Contains 800 sequences at various spatial resolutions from 270p to 2160p and has been evaluated on ten existing network architectures for four different coding tools.
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YT-UGC is a large scale UGC (User Generated Content) dataset (1,500 20 sec video clips) sampled from millions of YouTube videos. The dataset covers popular categories like Gaming, Sports, and new features like High Dynamic Range (HDR). This dataset can be used to study video compression and quality assessment.
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The Deep Fakes Dataset is a collection of "in the wild" portrait videos for deepfake detection. The videos in the dataset are diverse real-world samples in terms of the source generative model, resolution, compression, illumination, aspect-ratio, frame rate, motion, pose, cosmetics, occlusion, content, and context. They originate from various sources such as news articles, forums, apps, and research presentations; totalling up to 142 videos, 32 minutes, and 17 GBs. Synthetic videos are matched with their original counterparts when possible.
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