Automation Lab, Sungkyunkwan University

ETSS-06: Anomaly Detection

This is the official repository of

OpenAnomaly: An Open Source Implementation of Anomaly Detection Methods.

1. Setup

1.1. Using conda

1.1.1. Using environment.yml

conda env create -f envs/environment.yml
conda activate anomaly
pip install -e .

1.1.2 Using requirements.txt

conda create --name anomaly python=3.10.12
conda activate anomaly
pip install torch==1.13.1+cu117 torchvision==0.14.1+cu117 torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cu117
pip install -r envs/requirements.txt
pip install -e .

1.2 Using uv

uv venv anomaly --python=3.10.12
source anomaly/bin/activate
uv pip install -e .

2. Dataset Preparation

2.1. Industry Anomaly Detection Datasets

For the MVTec dataset, please download it from this link

For the BTAD dataset, please download it from this repository

For the VisA dataset, please download it from this repository

For the MVTec-Loco dataset, please download it from this link

For the MPDD dataset, please download it from this repository

For the DTD dataset, please download it from this link

For the DAGM dataset, please download it from this link

For the WFDD dataset, please download it from this repo

For the Real-IAD dataset, please download it from this link

For the MVTec3D dataset, please download it from this link

For the Eyecandies dataset, please download it from this link

For the MadSim dataset, please download it from this repository

For the Anomaly-ShapeNet dataset, please download it from this repository

For the Real3D-AD dataset, please download it from this repository

For the PD-REAL dataset, please download it from this repository

For the BrokenChairs dataset, please download it from this repository

For the ToysAD-8K and PartsAD-15K datasets, please download it from this repository

For the ELPV dataset, please download it from this repository

For the SDD dataset, please download it from this link

For the AITEX dataset, please download it from this link

For the Brain MRI dataset, please download it from this link

For the Head CT dataset, please download it from this link

For the Chest X-rays and OCT datasets, please download it from this link

For the ISIC2018 dataset, please download it from this link

For the Br35H dataset, please download it from this link

For the KSDD2 dataset, please download it from this link

for the MTD dataset, please download it from this repository

For the MulSen-AD dataset, please download it from this repository

For the 3CAD dataset, please download it from this repository

For the OCT2017 dataset, please download it from this link

For the APTOS dataset, please download it from this link

For the SensumSODF dataset, please download it from this link

For the infra 3DALv2 dataset, please download it from this repository

For the VAD dataset, please download it from this link

For the ContinualAD dataset, please download it from this link

For the GoodsAD dataet, please download it from this repository

For the M2AD dataset, please download it from this link

For the MVTec-2K dataset, please download it from this repository

For the ITDD dataset, please download it from this repository

For the MIP dataset, please download it from this repository

For the Kvasir-SEG dataset, please download it from this link

For the MMAD dataset, please download it from this repository

For the MTD dataset, please download it from this repository

For LiverCT, RESC, HIS, ChestXray, and OCT17 datasets, please download them from this repository

For the MiniShift dataset, please download it from this repository

For the MVTecQA dataset, please download it from this repository

For the BraTs2018 dataset, please download it from this link

For the ToysAD-8K dataset, please download it from this repository

For the 3D-ADAM dataset, please download it from this repository

For the RESC dataset, please download it from this repository

For the VID-AD dataset, please download it from this repository

2.2. Unsupervised Anomaly Detection Datasets

For UCSD Ped2, CUHK Avenue, and ShanghaiTech datasets, please download them from this repository

For the PAB dataset, please download it from this repository

For the HumanSAM dataset, please download it from this repository

For the Vad-R1 dataset, please download it from this repository

2.3. Video Anomaly Detection Datasets

For the ShanghaiTech dataset, please download extracted features from this repository.

For the UCF-Crime dataset, please download extracted features from this repository or repo.

For the UCF-Traffic dataset, please download extracted features from this repository

For the XD-Violence dataset, please download extracted features from this link.

For the TAD dataset, please download extracted features from this repository

For the UCA dataset, please download it from this repository

For the PreVAD dataset, please download it from this repository

2.4. Dashcam Traffic Anomaly Detection Datasets

For ROL and DoTA datasets, please download them from this repository

For CCD, DAD, and A3D datasets, please download them from this repository

For the DADA2000 dataset, please download them from this repository

For the W3DA dataset, please download it from this repository

For the VRU dataset, please download it from this repository

For the RoadSocial dataset, please download it from this repository

For the TrafficGaze dataset, please download it from this repository

For the MASKER_MD dataset, please download it from this repository

For the DADA-Seg dataset, please download it from this repository

For the DADA-1000 dataset, please download it from this repository

For the CUVA dataset, please download it from this repository

For the Russia Crash dataset, please download it from this link

For the TSOD10K dataset, please download it from this link

For the MM-AU dataset, please download it from this link

For the CrashChat dataset, please download it from this repository

For the AV-TAU dataset, please download it from this repository

2.5. Surveillance Traffic Anomaly Detection Datasets

For the TUMTrafficQA dataset, please download it from this repository

For the WWC dataset, please download it from this repository

3. Usage

3.1.1. Supported Models for 2D Industrial Anomaly Detection

Models	MVTec	BTAD	VisA	MVTec LOCO	MPDD	WFDD	Real-IAD	CIFAR-10	Fashion MNIST	KSDD2	SensumSODF	ContinualAD	EIDIs-SOD	CrackSeg9k	ZJU-Leaper	M2AD	MVTec-2K	APTOS	Kvasir-SEG	MTD	BraTs2018	RESC	VID-AD
CutPaste	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
SSAPS	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DRAEM	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
SPR	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
ADShift	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
FOD	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
PatchSVDD	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
CPR	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
FAIR	✔️	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
GLASS	✔️	❌	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
SimpleNet	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
SegAD	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
CDO	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
SPD	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
OnlineInReaCh	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
FUN-AD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
PBAS	✔️	❌	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MSAD	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
PANDA	❌	❌	❌	❌	❌	❌	❌	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
InReaCh	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
REB	✔️	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
HETMM	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
SuperSimpleNet	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Continual-Mega	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
WPFormer	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌
PADNet	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
M2AD	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌
LWinNN	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
ComAD	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
HiAD	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌
PatchGuard	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	❌	❌	❌	❌	❌	❌
UniNet	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	✔️	✔️	❌	❌	❌	❌
AnomalyNCD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	❌	❌	✔️	❌	❌	❌
COBRA	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	❌	❌	❌	❌	❌	❌
IPAD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	❌	❌	❌	❌	❌	❌
TailedCore	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	❌	❌	❌	❌	❌	❌
GLCF	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	❌	❌	❌	❌	❌	❌
TFA-Net	✔️	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	❌	❌	❌	❌	❌	❌
ADL4VAD	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	❌	❌	❌	❌	❌	❌
VarAD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	❌	❌	❌	❌	❌	❌
CostFilter-AD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	❌	❌	❌	❌	❌	❌
CLAD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	❌	❌	❌	❌	❌	❌
AnyAD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	❌	❌	❌	✔️	❌	❌
GCR	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	❌	❌	❌	❌	❌	❌
AR	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	❌	❌	❌	❌	✔️	❌
VID-AD	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	:z:	❌	❌	❌	❌	❌	✔️

3.1.2. Supported Models for 3D Industrial Anomaly Detection

Models	MVTec3D	Eyecandies	MadSim	Anomaly-ShapNet	Real3D-AD	BrokenChairs	PD-Real	MulSen-AD	infra 3DALv2	MIP	ToysAD-8K
BTF	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
CFM	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
CPMF	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Looking3D	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
M3DM	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
PAD	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌
Shape-Guided	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
SplatPose	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌
CRD	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
CMDIAD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MulSen-AD	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌
FPFHI	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌
EasyNet	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
Real3D-AD	✔️	✔️	❌	❌	✔️	❌	❌	❌	❌	❌	❌
3DSR	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
PO3AD	❌	❌	❌	✔️	✔️	❌	❌	❌	❌	❌	❌
MC4AD	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌
R3D-AD	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌
C3DAD	❌	❌	❌	✔️	✔️	❌	❌	✔️	❌	❌	❌
Reg2Inv	❌	❌	❌	✔️	✔️	❌	❌	❌	❌	❌	❌
MVR	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MC3D-AD	❌	❌	❌	✔️	✔️	❌	❌	❌	❌	❌	❌
PIAD	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌
GLFM	✔️	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌
ISMP	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌
SplatPosePlus	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌
CIF	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
PASDF	❌	❌	❌	✔️	✔️	❌	❌	❌	❌	❌	❌
RIF	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌
CASL	❌	❌	❌	✔️	✔️	❌	❌	❌	❌	❌	❌
Odd-One-Out	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️
BridgeNet	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
GS-CLIP	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
CMDR-IAD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
BTP-3DAD	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌

3.1.3. Supported Models for Anomaly Generative Industrial Anomaly Detection

Models	MVTec	BTAD	VisA	MVTec LOCO	MPDD	WFDD	Real-IAD	MVTec3D
Defect Spectrum	✔️	❌	❌	❌	❌	❌	❌	❌
DualAnoDiff	✔️	❌	❌	❌	❌	❌	❌	❌
MAGIC	✔️	❌	❌	❌	❌	❌	❌	❌
SeaS	✔️	❌	✔️	❌	❌	❌	❌	✔️
AnoStyler	❌	❌	❌	❌	❌	❌	❌	❌
O2MAG	✔️	❌	❌	❌	❌	❌	❌	❌

3.1.4. Supported Models for Diffusion Industrial Anomaly Detection

Models	MVTec	BTAD	VisA	MVTec LOCO	MPDD	WFDD	Real-IAD	MVTec3D
AnoDDPM	✔️	❌	❌	❌	❌	❌	❌	❌
D3AD	✔️	✔️	✔️	❌	❌	❌	❌	❌
DDAD	✔️	✔️	✔️	❌	❌	❌	❌	❌
DiAD	✔️	❌	✔️	❌	❌	❌	❌	❌
DiffAD	✔️	❌	❌	❌	❌	❌	❌	❌
DiffusionAD	✔️	❌	✔️	❌	✔️	❌	❌	❌
GLAD	✔️	❌	✔️	❌	✔️	❌	❌	❌
RealNet	✔️	✔️	✔️	❌	✔️	❌	❌	❌
AnomalyDiffusion	✔️	❌	❌	❌	❌	❌	❌	❌
TransFusion	✔️	❌	✔️	❌	❌	❌	❌	✔️
AnoGen	✔️	❌	❌	❌	❌	❌	❌	❌
InvAD	✔️	❌	❌	❌	❌	❌	❌	❌
MDPS	✔️	✔️	❌	❌	❌	❌	❌	❌
ReplayCAD	✔️	❌	✔️	❌	❌	❌	❌	❌
DGDM	✔️	❌	❌	❌	❌	❌	❌	❌
AnomalyAny	❌	❌	❌	❌	❌	❌	❌	❌
DeCo-Diff	✔️	❌	✔️	❌	❌	❌	❌	❌
CDAD	✔️	❌	✔️	❌	❌	❌	❌	❌
VLMDiff	✔️	❌	❌	❌	❌	❌	❌	❌
CCAD	✔️	❌	❌	❌	❌	❌	❌	❌
C3FGS	❌	❌	✔️	❌	❌	❌	❌	❌

3.1.5. Supported Models for Knowledge Distillation Industrial Anomaly Detection

Models	MVTec	BTAD	VisA	MVTec LOCO	MPDD	WFDD	Real-IAD	3CAD	APTOS	OCT2017	ISIC2018	VAD
DeSTSeg	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DMAD	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
EfficientAD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
IKD	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MemKD	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MixedTeacher	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MKD	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
RD	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
RD++	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
STFPM	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DAF	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
URD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
3CAD	✔️	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌
ReContrast	✔️	❌	✔️	❌	❌	❌	❌	❌	✔️	✔️	✔️	❌
SK-RD4AD	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	✔️
SCRD4AD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
AAND	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
SingleNet	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌

3.1.6. Supported Models for Large Language Models Industrial Anomaly Detection

Models	MVTec	VisA	MMAD	MVTecQA
AnomalyGPT	✔️	✔️	❌	❌
KAG-prompt	✔️	✔️	❌	❌
Echo	✔️	✔️	❌	❌
MMAD	❌	❌	✔️	❌
SAGE	❌	❌	❌	✔️

3.1.7. Supported Models for Memory Bank Industrial Anomaly Detection

Models	MVTec	BTAD	VisA	MVTec LOCO	MPDD	WFDD	Real-IAD	3D-ADAM
CFA	✔️	✔️	❌	❌	❌	❌	❌	❌
MemSeg	✔️	✔️	❌	❌	❌	❌	❌	❌
PaDiM	✔️	✔️	❌	❌	❌	❌	❌	❌
PatchCore	✔️	✔️	❌	❌	❌	❌	❌	❌
SPADE	✔️	✔️	❌	❌	❌	❌	❌	❌
SFRAD	✔️	❌	❌	❌	❌	❌	❌	❌
SA-PatchCore	✔️	❌	❌	❌	❌	❌	❌	❌
RAD	✔️	❌	✔️	❌	❌	❌	❌	❌

3.1.8. Supported Models for Multi-class Industrial Anomaly Detection

Models	MVTec	BTAD	VisA	MVTec LOCO	MPDD	WFDD	Real-IAD	MVTec3D	ITDD
CRAD	✔️	❌	❌	❌	❌	❌	❌	❌	❌
Real-IAD	✔️	❌	❌	❌	❌	❌	✔️	❌	❌
UniAD	✔️	❌	❌	❌	❌	❌	✔️	❌	❌
HVQ	✔️	❌	❌	❌	❌	❌	❌	❌	❌
MSTAD	✔️	❌	❌	❌	❌	❌	❌	❌	❌
MambaAD	✔️	❌	✔️	❌	❌	❌	❌	✔️	❌
ViTAD	✔️	❌	✔️	❌	❌	❌	❌	✔️	❌
InvAD	✔️	❌	✔️	❌	❌	❌	❌	✔️	❌
Dinomaly	✔️	❌	✔️	❌	❌	❌	✔️	❌	❌
RLR	✔️	❌	✔️	❌	❌	❌	❌	❌	❌
UniFormaly	✔️	❌	❌	❌	❌	❌	❌	❌	❌
OneNIP	✔️	❌	❌	❌	❌	❌	❌	❌	❌
IUF	✔️	❌	✔️	❌	❌	❌	❌	❌	❌
MoEAD	✔️	❌	✔️	❌	❌	❌	❌	❌	❌
PMAD	✔️	❌	❌	❌	❌	❌	❌	❌	❌
UniAS	✔️	❌	✔️	❌	❌	❌	❌	❌	❌
Omni-AD	✔️	❌	✔️	❌	❌	❌	✔️	❌	❌
LGC	✔️	✔️	✔️	❌	❌	❌	✔️	❌	❌
RAS	✔️	❌	❌	❌	❌	❌	❌	❌	❌
Wave-MambaAD	✔️	❌	✔️	❌	❌	❌	❌	✔️	❌
CRAS	✔️	❌	✔️	❌	✔️	❌	❌	✔️	✔️
AnomalyMoE	✔️	❌	❌	❌	❌	❌	❌	❌	❌
MVAD	❌	❌	❌	❌	❌	❌	✔️	❌	❌

3.1.9. Supported Models for Noisy Industrial Anomaly Detection

Models	MVTec	BTAD	VisA	MVTec LOCO	MPDD	WFDD	Real-IAD
SoftPatch	✔️	✔️	❌	❌	❌	❌	❌

3.1.10. Supported Models for Normalizing Flows Industrial Anomaly Detection

Models	MVTec	BTAD	VisA	MVTec LOCO	MPDD	WFDD	Real-IAD	MVTec 3D
AST	✔️	✔️	❌	❌	❌	❌	❌	✔️
BGAD	✔️	✔️	❌	❌	❌	❌	❌	❌
CFLOW-AD	✔️	❌	❌	❌	❌	❌	❌	❌
DifferNet	✔️	❌	❌	❌	❌	❌	❌	❌
HGAD	✔️	✔️	✔️	❌	❌	❌	❌	❌
MSFlow	✔️	✔️	❌	❌	❌	❌	❌	❌
PyramidFlow	✔️	✔️	❌	❌	❌	❌	❌	❌
DADF	❌	❌	❌	✔️	❌	❌	❌	❌

3.1.11. Supported Models for Out-of-Distribution Industrial Anomaly Detection

Models	MVTec	BTAD	VisA	MVTec LOCO	MPDD	WFDD	Real-IAD	Chest X-rays	OCT	ISIC2018	Br35H	UCF101	HMDB51	EPIC-Kitchens	Kinetics-600	VOC2017	COCO2017	CAMELYON17	APTOS
ADShift	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
GeneralAD	✔️	❌	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
CKAAD	✔️	❌	✔️	❌	❌	❌	❌	✔️	✔️	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌
MultiOOD	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	✔️	✔️	✔️	❌	❌	❌	❌
OLN-SSOS	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	✔️	❌	❌
VOS	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	✔️	❌	❌
RobustND	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	✔️	✔️	❌	❌	❌	❌	✔️	✔️	✔️	✔️
FiCo	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌

3.1.12. Our Industrial Anomaly Detection Models

Models	MVTec	BTAD	VisA	MVTec LOCO	MPDD	WFDD	Real-IAD
DM-GRD	✔️	✔️	✔️	❌	❌	✔️	❌

3.1.13. Supported Models for Segment Anything Industrial Anomaly Detection

Models	MVTec	BTAD	VisA	MVTec LOCO	MPDD	WFDD	Real-IAD
UCAD	✔️	❌	❌	❌	❌	❌	❌
SALAD	✔️	❌	❌	❌	❌	❌	❌
SAM-SPT	✔️	❌	❌	❌	❌	❌	❌

3.1.14. Supported Models for Supervised Industrial Anomaly Detection

Models	MVTec	BTAD	VisA	MVTec LOCO	MPDD	WFDD	Real-IAD
DevNet	✔️	❌	❌	❌	❌	❌	❌
PRNet	✔️	✔️	❌	❌	❌	❌	❌
DRA	✔️	❌	❌	❌	❌	❌	❌

3.1.15. Supported Models for Low-shot Industrial Anomaly Detection

Models	MVTec	BTAD	VisA	MVTec LOCO	MPDD	WFDD	Real-IAD	ELPV	SDD	AITEX	BrainMRI	HeadCT	DAGM	DTD	Br35H	ISIC	ColonDB	ClinicDB	TN3K	Real3D	Eyecandies	MVTec3D	MVTec-FS	KSDD2	MTD	GoodsAD	LiverCT	RESC	HIS	ChestXray	OCT17
WinCLIP	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
PromptAD	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
InCTRL	✔️	❌	✔️	❌	❌	❌	❌	✔️	✔️	✔️	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
AnomalyCLIP	✔️	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
APRIL-GAN	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
AdaCLIP	✔️	✔️	✔️	❌	✔️	❌	❌	❌	✔️	❌	✔️	✔️	✔️	✔️	✔️	✔️	✔️	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
PointAD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
AMI-Net	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
ResAD	✔️	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
MVP-PCLIP	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
VCP-PCLIP	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
AnoVL	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MVREC	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌
Segment-Any-Anomaly	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	✔️	✔️	❌	❌	❌	❌	❌	❌
CLIP-AD	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	✔️	✔️	❌	❌	❌	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
GPT-4V	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
FADE	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
AnomalyDINO	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
FiLo	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MetaUAS	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌
FoundAD	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
NAGL	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
CoDeGraph	✔️	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
AD-DINOv3	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
ReMP-AD	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
FAPrompt	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
RareCLIP	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MuSc	✔️	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DictAS	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Bayes-PFL	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MultiADS	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
AF-CLIP	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
TPS	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
RegAD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
AA-CLIP	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
INP-Former	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
LogSAD	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
IIPAD	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
LAFT	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
UniVAD	✔️	❌	✔️	✔️	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	✔️	✔️	✔️	✔️
Anomagic	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
AdaptCLIP	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
PCSNet	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DIVAD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
TF-IDG	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
UniADC	✔️	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Tipsomaly	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MRAD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
SubspaceAD	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
D24FAD	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
VisualAD	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
GATE-AD	✔️	❌	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌

3.2. Supported Models for Dashcam Traffic Anomaly Detection

Models	ROL	DoTA	CCD	DAD	A3D	CTA	DADA-2000	W3DA	VRU	RoadSocial	TrafficGaze	MASKER_MD	DADA-Seg	DADA-1000	CUVA	Russia Crash	TSOD10K	MM-AU	CrashChat	AV-TAU
AMNet	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Baseline GRU	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DSTA	❌	✔️	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
UString	❌	❌	✔️	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
XAI-Accident	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
CTA	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
TTHF	❌	✔️	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
W3DA	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
RARE	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
BADAS	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DriveCLIP	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DriveCLIP	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
PromptTAD	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
RoadSocial	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Hawk	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
CGNAM	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
SaliencyMamba	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
DRIVE	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
GSC	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌
MMUDA	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌
LOTVS-CAP	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌
LOTVS-CAAD	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌
Graph-Graph	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
CRASH	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
CUVA	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌
Ctrl-Crash	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌
Tramba	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌
LOTVS-MM-AU	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌
CrashChat	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	✔️	❌
EchoTraffic	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️

3.3. Supported Models for Unsupervised Anomaly Detection

Models	Avenue	ShanghaiTech	Ped2	Arbitrary Video	PAB	HumanSAM	Vad-R1
3DNet	❌	❌	❌	✔️	❌	❌	❌
GMM_DAE	✔️	✔️	✔️	❌	❌	❌	❌
Jigsaw-VAD	✔️	✔️	✔️	❌	❌	❌	❌
OGAM-MRAM	✔️	✔️	✔️	❌	❌	❌	❌
SwinAnomaly	✔️	✔️	✔️	✔️	❌	❌	❌
GenerateAnomaliesFromNormal	✔️	✔️	✔️	❌	❌	❌	❌
F2LM	✔️	❌	✔️	❌	❌	❌	❌
VADMamba	✔️	❌	✔️	❌	❌	❌	❌
AED-MAE	✔️	❌	❌	❌	❌	❌	❌
CMP	❌	❌	❌	❌	✔️	❌	❌
DDL	✔️	❌	❌	❌	❌	❌	❌
HumanSAM	✔️	❌	❌	❌	❌	✔️	❌
TAO	❌	❌	✔️	❌	❌	❌	❌
Vad-R1	❌	❌	✔️	❌	❌	❌	✔️

3.4. Supported Models for Surveillance Traffic Anomaly Detection

Models	UCF-Traffic	TAD	TSP6K	SO-TAD	TUMTrafficQA	WWC
TA-NET	✔️	✔️	❌	❌	❌	❌
TSP6K	❌	❌	✔️	❌	❌	❌
SO-TAD	❌	❌	❌	✔️	❌	❌
TraffiX-Qwen	❌	❌	❌	❌	✔️	❌
WWC-Predictor	❌	❌	❌	❌	❌	❌

3.5. Supported Models for Weakly-supervised Anomaly Detection

Models	Ten crops	Flatten crops	UCF-Crime	XD-Violence	ShanghaiTech	MSAD	ECA9	GTA-Crime	UCA	PreVAD
MIL	✔️	✔️	✔️	✔️	✔️	❌	❌	❌	❌	❌
RTFM	✔️	✔️	✔️	✔️	✔️	❌	❌	❌	❌	❌
WSAL	✔️	✔️	✔️	✔️	✔️	❌	❌	❌	❌	❌
GCN	❌	✔️	✔️	✔️	✔️	❌	❌	❌	❌	❌
MGFN	✔️	❌	✔️	✔️	✔️	❌	❌	❌	❌	❌
HyperVD	❌	✔️	✔️	✔️	✔️	❌	❌	❌	❌	❌
UR-DMU	❌	✔️	✔️	✔️	✔️	❌	❌	❌	❌	❌
BN-WVAD	❌	✔️	✔️	✔️	✔️	❌	❌	❌	❌	❌
CMA-LA	❌	✔️	✔️	✔️	✔️	❌	❌	❌	❌	❌
ARNet	❌	✔️	✔️	✔️	✔️	❌	❌	❌	❌	❌
MyModel	✔️	✔️	✔️	✔️	✔️	❌	❌	❌	❌	❌
MyModel1	❌	✔️	✔️	✔️	✔️	❌	❌	❌	❌	❌
MSAD	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌
SIAVC	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌
IEF-VAD	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌
VadCLIP	❌	❌	✔️	✔️	❌	❌	❌	❌	❌	❌
GTA-Crime	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌
AnomalyCLIP	❌	❌	✔️	✔️	✔️	❌	❌	❌	❌	❌
LAVAD	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌
UCA	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌
DSANet	❌	❌	✔️	✔️	❌	❌	❌	❌	❌	❌
LaGoVAD-PreVAD	❌	❌	✔️	✔️	❌	❌	❌	❌	❌	✔️

3.6. Supported Models for Feature Extraction

Models	RGB	Point Cloud	Depth	Text	Mask	Optical Flow	Audio	Stereo Matching	TIR	Video	Orient	Feature Matching	Surface Normal	Edge
C3D	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
I3D	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Dense Trajectory	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Foreground Mask	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
HoF	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
HoG	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Motion Boundary	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Motion Magnitude	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
TVL1	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Depth Anything	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Depth Anything V2	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DepthCLIP	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
LapDepth	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MegaDepth	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DepthFM	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Depth Pro	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Amodal Depth Anything	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Video Depth Anything	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
PatchRefiner	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MiDaS	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Structure-Guided Ranking Loss	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Distill-Any-Depth	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
supdepth4thermal	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
RollingDepth	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
UniDepth	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
TIDE	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MoGe	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MODEST	❌	❌	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
FocusOnDepth	❌	❌	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
PromptDA	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
GeometryCrafter	❌	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
UniK3D	❌	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Murre	❌	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
VGGT	❌	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
LiteVGGT	❌	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
RobustVGGT	❌	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
StreamVGGT	❌	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Prior-Depth-Anything	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
FlashDepth	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DepthAnything-AC	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MonSter	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DORNet	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DepthSplat	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DCL	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Monodepth	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Monodepth2	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
PWC-Net	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Lotus	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌
Lotus-2	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌
Marigold-DC	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DAC	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DA-2	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌
GeoWizard	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌
MVInverse	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌
Pixel-Perfect	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
HQ-SAM	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
AdaBins	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
BoRe-Depth	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Depth-Anything-3	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DAP	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
PanDA	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Genfocus	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DKT	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DA360	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
LingBot-Depth	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
PatchRefinerV2	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DVD	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
AnySplat	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
InfiniDepth	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
NVPanoptix-3D	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
CLIP	✔️	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
LongCLIP	✔️	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
MobileCLIP	✔️	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
OpenCLIP	✔️	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
TinyCLIP	✔️	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
RWKV-CLIP	✔️	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
FastVLM	✔️	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
LeGrad	✔️	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Perception Models	✔️	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Spatial-CLIP	✔️	❌	✔️	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Segment-Anything	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
Segment-Anything-v2	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
SegmentAnyRGBD	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
mm-sam	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
cat-sam	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
TinySAM	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
CLIPSeg	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
RobustSAM	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
DIS	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
U-2-Net	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
BASNet	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
Point-E	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
VGGT-Long	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Utonia	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
EVF-SAM	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
Grounded-SAM-1	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
Grounded-SAM-2	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
LENS	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
EdgeTAM	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
UnSAMv2	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
SAM3	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
SAM3D	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
SAMWISE	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
DiffusionVAS	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
Semantic-SAM	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
CutLER	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
TokenCut	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
SAM3-DMS	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
OpenSeeD	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
GeoMotion	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
Fast-SAM-3D-Body	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
AlphaCLIP	✔️	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
RAM	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
Marigold	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
ZoeDepth	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
DepthCrafter	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
AnyDepth	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌
NeuFlow v2	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌
RAFT	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌
Flow-Anything	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌
GMFlow	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌
UniMatch	❌	❌	✔️	❌	❌	✔️	❌	✔️	❌	❌	❌	❌	❌	❌
FastFlowNet	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌
FlowNet	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌
ReCoVEr	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌
WAFT	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌
DPT	❌	❌	✔️	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
FastSAM	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
MobileSAM	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
Segmenter	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
UISE	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
YOSO	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
OpenWorldSAM	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
X-Decoder	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
UniPixel	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
SEEM	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
Ref-SAM3D	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
VideoMaMa	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
RESAnything	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
SAM4MLLM	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
SAMTok	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
gen2seg	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
DecAF	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
Fast-SAM3D	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
SAAS	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
CoT-RVS	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌	❌	❌
ImageBind	✔️	❌	✔️	✔️	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌
FoundationStereo	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌
ZeroStereo	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌
S2M2	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌
GGEV	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌
StereoAnyVideo	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌
Fast-FoundationStereo	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌
sRGB-TIR	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌
Video Features	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌
Orient-Anything	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌
Orient-Anything-V2	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌
LiftFeat	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌
MINIMA	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌
EDM	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌
RoMa	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌
RoMav2	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌
OmniGlue	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌
MASA	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌
MATCHA	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌
L2M	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌	❌
DSINE	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌
NormalCrafter	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌
StableNormal	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌
TransNormal	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️	❌
PiDiNet	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	❌	✔️
SAM-Audio	❌	❌	❌	❌	❌	❌	✔️	❌	❌	❌	❌	❌	❌	❌

3.7. Supported Models for AI City Challenge

Models	Iowa DOT
CETCVLAB	✔️
SIS_Lab	✔️

3.7. Supported Models for Extension Research

Architectures

Attention Modules

Convolution Architectures

Generative Models

Geometric Models

Losses

Token Mixer Models

Optimizer

Transformer Models

UNet Models

3D Reconstruction Models

MoE Models

Mamba Models

KAN Models

Implicit Neural Representations Models

Low-rank Decomposition Models

Neural Operator Models

Spiking Neural Networks/Event camera Models

Efficient Models

Vision Language Models

Neural ODE Models

OT Models

Flow Matching Models

Visualization Models

Image Captioning Models

Knowledge Distillation Models

Domain Generalization Models

Data Augmentation Models

Object Detection Models

Physics Models

Representation Learning Models

RWKV Models

Referring Expression Models

Scene Graph Generation Models

World Models

Hopfield Models

Brain-inspired Models

Image Editing Models

Image Similarity Models

Active Learning Models

Upsample Models

Autoregressive Models

CSZL Models

Segmentation Models

In-Context Learning Models

Continual Learning Models

Toolbox

Energy Models

Dataset Distillation Models

Reinforcement Learning Models

Quantum Models

Test-Time Training Models

A2 Attention ACmix Attention AFT Attention Agent Attention Attention on Attention Axial Attention Axial Attention BAM Attention Bidirectional Cross Attention CBAM Attention CoAtNet Attention Compositional Attention Coord Attention CoT Attention CrissCross Attention Crossformer Attention DANet Attention DAT Attention Deformable Attention ECA Attention EMSA Attention External Attention Flash Transformer Attention GFNet Attention GSA Attention Halo Attention Hamburger Attention Kronecker Attention LambdaNet Attention Linformer Attention Local Attention MOA Transformer MobileViT Attention MobileViTv2 Attention MUSE Attention Non-local Attention Nystrom Attention Outlook Attention ParNet Attention PolarizedSelf Attention PSA Attention Residual Attention S2 Attention SCSE Attention Self-attention SGE Attention Shuffle Attention SimAM Attention Simplified Self-attention SK Attention Slot Attention Taylor Linear Attention Triplet Attention UFO Attention ViP Attention Ring Attention Hierarchical Attention Rectified Linear Attention Space Time Attention Halo Attention Coordinate Descent Attention Memory Compressed Attention Mega Attention Tranception Attention Infini Attention Sparse Attention Multi-modal Cross Attention Attention with Convolution MoA LinearAttentionTransformer Performer ISAB MemoryEfficientAttention Perceiver CoLT5-attention GatedSlotAttention JVP CBSA MCA

Dynamic Convolution Wavelet Convolution Invertible Residual Networks FrEIA Fast Feedforward Networks GLOM Firefly Bayesian Enhancement Model Minimalist Vision with Freeform Pixels AKOrN Any-Precision Deep Neural Network FDConv OverLoCK ConvNeXt HSNet Homeostatic Neural Networks VAT NC-Net ANCNet CVNet ConverseNet ConvNeXt-V2 FFC Contextual-Convolutional-Networks CoConv LogViG Optical-FCNN FDAM SN-Net Nested-Learning CycleMLP SimSiam TRL DDL V4D BayesianCNN F-Conv

EMA Vector Quantization VQ-VAE TiTok DiT Fast DiT DTR ANT R3GAN DALL-E VAR CleanDIFT Vec2Vec FoD taming-transformers DiS MAR DiCo Tweedie EnergyMatching DDPM Guided-Diffusion Improved-Diffusion FSDDIM DDIM RectifiedFlow GMFlow ScoreSDE FlowGrad InstaFlow EDTR TorchCFM RAE CSBM REPA InDI U-ViT DiffMoE MDM JiT DDT SiT FractalGen CoDe DAAM Glance ViBT TREAD MaskDiT EDM ToMe Open-Sora REPA-E LearningWithNoise S-NODE LTX-Video MobileI2V Next-Patch-Prediction DimensionX Cosmos-Predict2.5 DeepVerse Cosmos-Transfer2.5 Wan2.2 CogVideo LTX-2 DiT-Extrapolation Self-Refining UniVideo FlashWorld PixelGen FastVMT REPA-G DummyForcing CSBM MVAR EAR Drifting LongLive Self-Forcing Driftin FlowCache LayerSync Spacetime-Diffusion Mobile-O RollingSink CHORDS Helios DiffiT WAE

geoopt HCL Hyperbolic CV Hyperbolic Embedding Hyperbolic Vision Transformer meru HCL Poincare Resnet HypMix Curvature Generation CO-SNE HypAD HVT HiHPQ GM-VAE GHSW DOHSC-DO2HSC GW-Regularization Hypformer HAE HYSP HR-MLP hierahyp HypLiLoc UnHyperML HypStructure HierarchyCPCC CIDER HYPE DMT-HI HHCH hypvl hycoclip HyProMeta LResNet Hyperbolic Wrapped Distribution pvae DistilVPR HypHC L3DMC GPr-Net Longtail Segmentation Hyperbolic Feature Augmentation hyperfuture CurAML BREEDS OTCPCC HPEC QCNN CLIP-M3 Hyp-OW AngularGap vMF Rotation_Trick HySAC QRNN QCLNet Quaternion-Capsule-Networks QGAN HSN HyCoRe HLFormer HOVER HyperCLIP HypCD HS-DTE HypGCD H-CLIP ATMG Geo-Sign HAMN HexFormer PHyCLIP Hyperbolic_Interpretability HIVE HoroPCA HypModalAlign HypPNet HIDISC HDD HypDAE HyperRL Graph-Prompt HypLL Hyperbolic-Vim phier MGIoU Hyperbolic_Action CQH WMDD HybCBC HBNN

OT CLIP GradNorm

gMLP MLP Mixer Segformer ResMLP ActiveMLP

Adam Atan 2 AdaMod Adan Lion Gradient Ascent Decoupled LionW Gradient Equillibrum Computer Vision Model Compression Techniques Grokfast AdEMAMix SlimAdamW CAME Sophia VRADAM NL_Optimizers

Rotary Embedding Transformer in Transformer Spline-based Transformers DyT Diff-Transformer ELN MAE PVT Vision_GNN DINO DINOv2 RC-MAE VGP EoMT SwinIRDehaze FasterViT Twins Deformable-DETR DETR ConditionalDETR MetaFormer HcNet DINOv3 HyperMAE RoPE-ViT SparK SBT PH-Reg JAFAR MultiMAE Vision-LSTM DinoUNet SegDINO MedDINOv3 REOrder LIT MedicalMAE Attention-Transfer Test-Time-Register PolaFormer BRIXEL ThinkingViT Franca SMCA-DETR ChangeDINO CRATE DReX RADIO CARE_Transformer FGTS SnapViT FractalDB Derf POA Pixio NEPA Co2S ALViT DAB-DETR MDETR DN-DETR MobileViT SSMAE CAS-ViT EdgeNeXt LoRA-DETR DIFFSSR ViT-Plasticity DINOv3_Animal AdaptOVCD Raptor ViT-5 MLLA LAST-ViT DiT4SR LocAtViT FastDINOv2 BinaryAttention AdapterTune HAViT PlaneCycle

Uformer Reversible U-Net X-UNet MIMO-UNet UNetv2 SAM3-UNet SAM2-UNet SAM-UNet SAM2-UNeXT Hyperbolic-U-Net

2D Gaussian Splatting 3D Gaussian Splatting iNeRF NeRF SyncDreamer D2GV GaussianImage Easi3R VGGSfM DUSt3R Fast3R MBPR GroupRec PromptHMR CrowdRec 2DGS_Inpaint GSASR ContinuousSR DeblurGS Deblur-NeRF BAD-Gaussians CLIPNeRF CLIP2NeRF nerfstudio SpikeNeRF gsplat NerfAcc Human3R 4DGaussians MapAnything UFM MuM SAM-Body4D HSMR Sharp Multi-View-Foundation-Models Pi3 DVGT EgoX PedGen VGGT4D InfiniteVGGT DroneSplat WorldGen LiftImage3D MASt3R Gen3R UniSH instant-ngp EasyVolcap 4K4D V-DPM Geo4D MonST3R MVGGT LongSplat GaussianSR Instant-GI LIG IGGT VeGaS GSVC 4DGS GaussianToken D-NeRF Deformable-3D-Gaussians SAT-HMR FastGS DashGaussian FastVGGT Shape-of-Motion Deblur4DGS Any4D JOSH MotionCrafter und3rstand GaussianImage++ ODE-GS LangSplat LangSplatV2 4DLangSplat UBS OmniVGGT AMB3R Flow3r CUT3R GT2-GS MoE-GS SGI LoGeR Mobile-GS LASER NanoGS MatryoshkaGaussianSplatting QuantVGGT PAGE4D

MoE CNN Soft MoE ViT Soft MoE PEER ST MoE Sparse MoE LIMoE MoD MoE Mamba Multi-Head MoE MoNE MoE-Fusion MoE Sinkhorn Router BlackMamba MoU Switch MoE DiT MoE TC-MoA Tutel MoSE M4oE NID FAME MVMoE Switch-DiT ScatterMoE SFAN SMoE DeepMoE GMoE MoFME ShiftAddViT MoA MoE-PromptCL CRMoE MoE Jetpack muMoE CLIP-MoE MoH MoE-Adapters4CL DAMEX Neural-Experts ConsistentMoE Mod-Squad DMP AMIR Efficient-WEMoE PnD weight-ensembling_MoE MEGAN DeMo SM3Det MEASNet SeemoRe MoCE-IR AdaptIR pFedMoAP Earth-Adapter DM-Adapter MicarVLMoE MFG-HMoE QuARF LFME MixBridge EMOE LiveEdit Beyond Parameter Count VMoBA I2MoE MoPE Diff-Retinex++ Inter2Former MoE-FFD BMFH-Net MFRNet BIG-MoE Robust-MoE-CNN JTDMoE Diff-MoE ICL Face-MoGLE AMoED Switch-NeRF T-MoENet MoE-Adapters++ MiN MINGLE HotMoE R-MoE DynMoE EMoE MoME MoE_CL AVMOE DeMoE SMoPE GM-MoE SPMTrack SFAN Forensic-MoE HyMoENet APMoENet MCMoE MoMKE CoMoE LPMoE EfficientMoE STAR GeoMoE AMOE DMDNet D-MoLE PA-MoE Gazeformer Meta-Expert ProMoE MoETTA WMNet DMFusion GRAM Point-MoE GazeMoE CA-MoE MEGADance LE-ProtoPNet MedMoE M4Fuse StyleExpert SpecMoE VidPrism

MambaVision TinyViM VM-UNet TransMamba Vim Vamba MobileMamba DAMamba CLIMB-ReID Mamba-Reg MambaOut MAP ARM LFTramba PoinTramba Tran-Mamba Dimba MxT HMT-Unet VM-UNetv2 AiM CWNet FreqMamba LocalMamba VMamba RetinexRawMamba W-Mamba VMatcher SP-Mamba M3amba Mamba3D HSRMamba WalMaFa Wave-Mamba IRSRMamba MambaIR DFSSM FreMamba MambaLLIE VCMamba V2M BMTNet PRISM AdaSFFuse MambaMoE SpectralVMamba EAMamba WDMamba CAB MambaHoME VSSD AFM-Net SFMFusion ReIDMamba MatMamba TPCM-SegNet NDMamba MM-DETR TranSamba ACMamba CMFS UVM-Net Dino-Mamba TimeViper Mamba-3 EQ-VMamba

Efficient KAN Vision KAN Fast KAN Fourier KAN MoE KAN KAT GR_KAN KAN COIN KM_UNet U-KAN MedViTV2 RKAN FewSound KAN-AD LDSB cmKAN KAC KArAt QKAN KAN-IDIR JacobiKAN ChebyKAN GroupKAN ABFR-KAN FasterKAN DGKAN ViK

siren CoLIE WIRE NeRCo GKAN SCONE LINR FR-INR NeRD INRAD SineKAN NeRP MINER O-INR ImpSq ANR Partition INR COIN LoE FreSh RFF FINER FINER++ xinc Deblur-INR Trans-INR GINR-IPC Local-Global-INR NeRV HNeRV NerPE IRL-INR DI-INR LIIF awesome QIREN COMBINER RECOMBINER TAF nir INR-Harmonization BDINR VideoINR PFNR DINER TSINR CQ-NIR Sobolev_INRs Poly_INR INR-ST O2V SketchINR INR-ECGAN LTE HNET LTEW PartSDF Spherical-INR UncertaINR LosslessINR DDiF SAPE Symmetric-Power-Transformation-INR MWT HiNeRV NG NFN EVOS-INR INT FAOR SNF RPP NeuralSVG STINR FeINFN Spener Moner VI3NR PhysINR IGA-INR MetricGrids NeuRBF HyperNVD SL2A-INR NeRT Implicit-Zoo INRFlow Transformer-NFN SIREN-square INF FFN INR-benchmark Residual-INR STAF INCODE FFNeRV Neural-Knitworks IDIR MetaSeg CLIT STRAINER SUICA INR-Bench NeuroQuant CST-Net LINR-PCGC Split-Layer MFSR-CD COIN++ REFINE-MORE DINo HUVR DInf-Grid ASSR LGE_INR CNS_INR SIR-SNC NINT CAFE Lipschitz-INR TorchLip TeCoNeRV Equivariant-ASISR

LoRA PEVC MLoRE LoRA-IR CLIP-LoRA LoME MoRA DeLoRA ASI DyLoRA-MoE SR-LoRA LoRA-ViT BiLaLoRA

Fourier Neural Operator UNO U-FNO G-FNO AFNO HiNOTE SRNO Fourier Imaging Galerkin-type Self-attention Factorized Fourier Neural Operator NeuralOP Latent Neural Operator Wavelet Neural Operator Derived-Quanities Fourier Neural Operator FNO Multi Sized Images AAAI FNO Tutorial MAWNO NeurOp-Diff AMG CoNO FNOReg CGH-SFO AFFNet DAFNO Geo-FNO ResFNO GNOT SSRNO INN FNIN UNet-FNO WDNO SFNO GANO NewtonFNO PITA DPOT PINO VINO GKN PAC-FNO PDIO MambaNO muTransfer-FNO RNO iFNO UNOI CNO HNOSeg-XS JPNeO-XS NeurOLight PastNet PINN_FP64 TANTE Tucker-FNO AFNO DINOZAUR STVSR-NO INO OpFlow PODNO MINO HyPINO RINN SPL_OFM MoEPOT SoFoNO FNOPE FlowGINO MMGN Sonnet NeuralKoopmanSVD PINN PINNs-Torch R-FNO SONIC IRNO DisentangO DRIFT-Net NOIR

SpikeYOLO EMS-YOLO SpikingYOLO EOLO RENet DSEC-MOS RVT LEOD SSM SMamba eTraM SpikingYOLOX MvHeatDET CvHeat-DET DAGr SU-YOLO CREST DEOE SNNTracker Advanced-SpikingYOLOX TDE LISNN E-SpikeFormer Meta-SpikeFormer Spike-driven Spikformer QKFormer SEW_ResNet SpikingResformer SEMM Spikingformer CML SGLFormer NDA_SNN MS-ResNet SWformer BKDSNN Event_Modality_Application EventCLIP EST EDP n_imagenet SpikeCLIP NeuroCLIP SLAYER T-RevSNN GAC SpikeVideoFormer SpikMamba ExACT EventBind NVS2Graph ANN2SNN_NQ MambaPAR SNN-PAR VTB EventMamba TET STMixer MTT SML MaxFormer Masked-Spiking-Transformer AT-LIF TRSG CKDSNN Mamba-Spike SpiLiFormer BSDSNN PseudoSNN DSD STOD SGC BSD DeepEISNN EnhSNN MSViT e2vid EvINR ESDNet SpikerIR NER EventGAN EHN EVSNN SpikeCLIP INR-Event-VSR PRE-Mamba DepthAnyEvent e2depth Spike-FlowNet RSIR e2flow SpikeDiffusion EvEnhancer DehazeSNN VLIF Gen1_toolbox V2CE V2E Vid2E S2R IEBCS I2E UCF-Crime-DVS ISSAFE EventAD Spike2Former SLTNet ECOS Spiking-DeepLab MambaSeg HARDVS HARDVSv2 SPM

mincam NdLinear GlobustVP minGRU OFA MobileOne MobileIE Turbo-VAED PreciseRoIPooling ortho-residual MobileNetV4 MobileNetV3 MobileNetV2 MobileNetV1 RepViT EfficientFormer LeViT MobileViG MobileViGv2 GreedyViG Mobile-U-ViT AB-BNN BPAM LGM Lottery-Ticket-Hypothesis mHC Titans Flash-KMeans

CoOp CLIP_Surgery PromptKD MCM CLIP-KD MaPLe DPLQ DiffCLIP DualPrompt PromptSRC DualCoOp MMRL Safe-CLIP CLIP-Refine Tip-Adapter TrustVLM Bayesian-Prompt-Learning Nano-vLLM PointCLIP PromptFix CAT-Seg DMN FCPrompt SurPL MITLOp-CCAug GCSCoOp PromptAlign CasPL TAP AToken KgCoOp ProGrad CLIPstyler MSAE Mobile-VideoGPT NXTP minGPT iGPT AdaptVision ICL SuperCLIP MoPD PAE PDA

CLODE DeepRUOT NeuralODE SDE SNOpt RNODE ANODE GAINS DCN NODE-ImgNet DMF NODEO NODE-GP CLE ResNet_NODE HomoODE MetaNODE Bi-flow HazeFlow DEQ FLUX-IR

Hyperbolic Alignment PLOT DUCT OT Fusion TransformerFusion Intra-Fusion LAVCap Tree-based Diffusion Schrödinger Bridge OTCE TSA-MLT OT-VP LICO SinkhornAutoDiff FedOTP ALIGN TCL DebiasedOT MGPATH COT APTP HiWA MM-Align AWT PROP L2RM KPG-RL OSSL Prompt-OT NLPrompt AffScoreDeep OTSeg Sinkformers DiffusionSchrodingerBridge LightSB-Matching LightSB OTTER EntropicOTBenchmark RAM DbTSW ASOT TOT DoRA MFSWB DA-RCOT TRIP REMOTE UniOT UNSB CUNSB-RFIE DehazeSB LaCoOT CatSBench BaryIR RCOT SOT-GLP SOTA

LieFlow FM PnP-Flow SemFlow Data-Uncertainty FlowMatching EqM FFM DeltaFM Flow-Guidance MeanFlow TCCM RFM ATFM Restora-Flow BFM PCFM FERNN SoFlow flowNP PBFM DegFlow Self-Flow VGG-Flow

Finer-CAM VCC MoXI Prompt_CAM CLIP-dissect WWW Transformer-Explainability MAMMI SIC NWHead ProTeCt B-cos-v2 VPS FIxLIP Grad-Eclip exCLIP Lucent TAM CE-FAM FG-VCE EPIC VX-CODE ConceptAttention MaskInversion Fusion-CAM FaCT DEX-AR SCAN

describe-anything KGG kg-gen Cosmos-Reason2 CogVLM2 CogVLM Qwen3-VL LLaVA LLaVA-3D LLaVA-Grounding MiniGPT-4 Youtu-VL

mean-teacher MM-DistillNet CSKD Manifold_Distillation CMT DM2TNet LMT-GP

L2D DANN D_GCD PromptStyler DPStyler DFCF PromptTA SFDG RobustNet ABA ALT DDG NeuralLio ASRNorm PDEN SFDA2 MJDOT Fish ZeroShotDG M-ADA

AFA HybridAugment++ SPM VIPAug DCAug PhysAug RainNet InstanceAugmentation Polar_Augment NMCB FastAutoAugment RandAugment Analytical-Learning-Theory On-Device-DG MixStyle XDomainMix RandConv SagNet C-UDA LEAwareSGD ConDiSR StyDeSty ADA EFDM AdaIN CCDR FIXED OpenDG-DAML LearnAug-UDA TeachAugment TTSA TSA DoGE MIXALL FreeSDG UDA-norm-VAE OnlineAugment FATA Mixup_for_UDA

UniFS OLN SR4IR DEIMv2 Rex-Omni AutoEval GroundingDINO Open-GroundingDino GSDet DEQDet YOLO-Master YOLO-IOD SAM-DETR

PSF-Estimation MANO PhyDNet vHeat CIConv PhyDAE NLOS-LPP QuantiPhy PhysVideoGenerator PhysCtrl PhysDreamer NCLaw NewtonGen STDDN Goal-Force PhysicEdit RealWonder UWEnhancer

ICon MRL Pigment_Representation VAC RotationContinuity UAE Platonic KnowCoL Midway FlowFeat Compositional-Generalization

CRWKV Vision-RWKV Restore-RWKV RWKV-UNet VisualRWKV RWKV-IR Diffusion-RWKV LION OmniRWKVSR URWKV LALIC FEAT ScaleMatch HFE-RWKV OccRWKV LF-RWKVNet EventPAR ChangeRWKV RWKV-VG RetinexRWKV RWKVFusion RSRWKV GDSR RWKVSR FRWKV Fourier-RWKV Hi-RWKV TS-Pan DIN-GEBC RawRWKV DRWKV MMSegRWKV LHIC-BP LineRWKV PointRWKV

RMOT CRMOT TempRMOT RexSeek 3EED WildRefer Dynamic-MDETR TransVG RefDrone SOREC Zeroshot_REC RefCrowd OmniSegNet ReLA GPT4RoI DKGTrack FlowRVS

SARD EGTR USGG sg2im Graph-RCNN OvSGTR Seg-Grounded OpenPSG Pair-Net VLPrompt HiLo Fair-PSGG Scene-Graph-ViT REACT PL TDE PENET TopoNet T2SG Salience-SGG

I-JEPA V-JEPA V-JEPAv2 JEPA_SSL PiLaMIM SCOTT D-JEPA Point-JEPA CNN-JEPA CNN-JEPA DINO-Foresight FUTURIST JEPA-T seq-JEPA LeJEPA FlowJEPA DMT-JEPA JEPA-Physics DSeq-JEPA TesserAct NanoJEPA LingBot-World EB_JEPA Rectified_LpJEPA EchoJEPA Newton-Kepler Infinite-World C-JEPA NeoVerse WorldGrow Social-JEPA BiJEPA HJEPA-MoE SAT-JEPA-DIFF

Hopfield-Layers Associative-Transformer iMixer

Neurons ZEBRA Lp-Convolution PhiNets PhiNetv2 NICE Brain-inspired-Replay SPM Pixel-Reg NeuroBridge TMNs FSPT-FSCIL ML-BVAE BraVL IterativeVAE HiCL VCFlow NeuroPictor

InstructPix2Pix Insert-Anything

VisDiff relsim

APL PCB PCoreSet CALD AL LabelBench EADA TQS SDM RIPU A2LC ALC SUGFW NAS TypiClust SCAN UHerding ISOAL CSQ BADGE PT4AL PPAL BLAD BGADL AL-consistency ALFA-Mix PAL CAMPAL LADA SAAL DiaNA AutoAugment UWE ActGen CAL AccuACL E2OAL BalancedEntropy HALO DG_AL CEG ELDA ASTE-AL

UpsampleAnything LoftUp FeatUp AnyUp NAF FeatSharp LiFT UPLiFT

AutoregressiveSegmentation

TOMCAT

RD-Net SegEarth-OV-3 CrowdSAM SAM-DAQ SAM3-Adapter DINO-AugSeg FSSDINO VidEoMT

AWRaCLe

CL_all-in-one LEAR ARCL-ViT QGPM GPM FIRE ACL PILOT Low-rank-CL InfLoRA SD-LoRA CL-LoRA AFEC IDER

SGG-Annotate CrowdSAM LabelAny3D SAM3D-Body-Rerun Paper2Rebuttal AutoFigure Intrinsic Autoresearch

EBMs_Jarzynski TEA Hyper-SET EBT EBTSA ET EBM_CL EBCLR JEM GeneralizedEBM Discrete-EBM EB_GFN HeatOOD

Dataset-Distillation

RL-AWB

TorchQuantum QuantumGS

ViTTT TTT TTT-MAE TTT-Video TTT_Denoising NCTTT TTT_Matching_VOS ITTT DATTT TTA Learning-Loss-TTA TTAch MTA GPS-TTA CI-TTA FSL FSL-Rectifier DynTTA MEMO MV-ATTA RLCF tttLRM TPT O-TPT C-TPT Vision-TTT A-TPT IMSE

4. Citation

If you find our work useful, please cite the following:

@misc{Chi2023,
  author       = {Chi Tran},
  title        = {OpenAnomaly: An Open Source Implementation of Anomaly Detection Methods},
  publisher    = {GitHub},
  booktitle    = {GitHub repository},
  howpublished = {https://github.com/SKKUAutoLab/ETSS-06-Anomaly},
  year         = {2023}
}

5. Contact

If you have any questions, feel free to contact Chi Tran (ctran743@gmail.com or tdc2000@skku.edu).

6. Acknowledgement

Our framework is built using multiple open source, thanks for their great contributions.