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‎tensorflow_datasets/testing/metadata/aflw2k3d/1.0.0/dataset_info.json‎

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{
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"citation": "@article{DBLP:journals/corr/ZhuLLSL15,\n author = {Xiangyu Zhu and\n Zhen Lei and\n Xiaoming Liu and\n Hailin Shi and\n Stan Z. Li},\n title = {Face Alignment Across Large Poses: {A} 3D Solution},\n journal = {CoRR},\n volume = {abs/1511.07212},\n year = {2015},\n url = {http://arxiv.org/abs/1511.07212},\n archivePrefix = {arXiv},\n eprint = {1511.07212},\n timestamp = {Mon, 13 Aug 2018 16:48:23 +0200},\n biburl = {https://dblp.org/rec/bib/journals/corr/ZhuLLSL15},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n",
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"description": "AFLW2000-3D is a dataset of 2000 images that have been annotated with image-level\n68-point 3D facial landmarks.\nThis dataset is typically used for evaluation of 3D facial landmark detection\nmodels. The head poses are very diverse and often hard to be detected by a \ncnn-based face detector.\nThe 2D landmarks are skipped in this dataset, since some of the data are not\nconsistent to 21 points, as the original paper mentioned.\n",
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"http://www.cbsr.ia.ac.cn/users/xiangyuzhu/projects/3DDFA/main.htm"
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‎tensorflow_datasets/testing/metadata/aflw2k3d/1.0.0/image.image.json‎

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{"encoding_format": "jpeg", "shape": [450, 450, 3]}

‎tensorflow_datasets/testing/metadata/cnn_dailymail/bytes/1.0.0/article.text.bytes‎

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### ByteTextEncoder
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### Metadata: {}

‎tensorflow_datasets/testing/metadata/cnn_dailymail/bytes/1.0.0/dataset_info.json‎

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"citation": "@article{DBLP:journals/corr/SeeLM17,\n author = {Abigail See and\n Peter J. Liu and\n Christopher D. Manning},\n title = {Get To The Point: Summarization with Pointer-Generator Networks},\n journal = {CoRR},\n volume = {abs/1704.04368},\n year = {2017},\n url = {http://arxiv.org/abs/1704.04368},\n archivePrefix = {arXiv},\n eprint = {1704.04368},\n timestamp = {Mon, 13 Aug 2018 16:46:08 +0200},\n biburl = {https://dblp.org/rec/bib/journals/corr/SeeLM17},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n@inproceedings{hermann2015teaching,\n title={Teaching machines to read and comprehend},\n author={Hermann, Karl Moritz and Kocisky, Tomas and Grefenstette, Edward and Espeholt, Lasse and Kay, Will and Suleyman, Mustafa and Blunsom, Phil},\n booktitle={Advances in neural information processing systems},\n pages={1693--1701},\n year={2015}\n}\n",
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"description": "CNN/DailyMail non-anonymized summarization dataset.\n\nThere are two features:\n - article: text of news article, used as the document to be summarized\n - highlights: joined text of highlights with <s> and </s> around each\n highlight, which is the target summary\n",
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‎tensorflow_datasets/testing/metadata/cnn_dailymail/bytes/1.0.0/highlights.text.bytes‎

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### ByteTextEncoder
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### Metadata: {}

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