Video-to-Video Synthesis
Learning a mapping function from an input source video to an output video.
( Image credit: vid2vid )
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Greatest papers with code
Video-to-Video Synthesis
NeurIPS 2018
• NVIDIA/vid2vid
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We study the problem of video-to-video synthesis, whose goal is to learn a mapping function from an input source video (e. g., a sequence of semantic segmentation masks) to an output photorealistic video that precisely depicts the content of the source video.
SEMANTIC SEGMENTATION VIDEO PREDICTION VIDEO-TO-VIDEO SYNTHESIS
Few-shot Video-to-Video Synthesis
NeurIPS 2019
• NVlabs/few-shot-vid2vid
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To address the limitations, we propose a few-shot vid2vid framework, which learns to synthesize videos of previously unseen subjects or scenes by leveraging few example images of the target at test time.
Deep Video Inpainting
CVPR 2019
• mcahny/Deep-Video-Inpainting
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Video inpainting aims to fill spatio-temporal holes with plausible content in a video.
IMAGE INPAINTING VIDEO DENOISING VIDEO INPAINTING VIDEO-TO-VIDEO SYNTHESIS
Deep Blind Video Decaptioning by Temporal Aggregation and Recurrence
CVPR 2019
• shwoo93/video_decaptioning
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Blind video decaptioning is a problem of automatically removing text overlays and inpainting the occluded parts in videos without any input masks.