Video-to-Video Synthesis
Learning a mapping function from an input source video to an output video.
( Image credit: vid2vid )
Leaderboards
| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
|---|---|---|---|---|---|---|
|
||||||
|
Greatest papers with code
Video-to-Video Synthesis
NeurIPS 2018
• NVIDIA/vid2vid
• 
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
•
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 Blind Video Decaptioning by Temporal Aggregation and Recurrence
CVPR 2019
• mcahny/Deep-Video-Inpainting
•
Blind video decaptioning is a problem of automatically removing text overlays and inpainting the occluded parts in videos without any input masks.
Deep Video Inpainting
CVPR 2019
• mcahny/Deep-Video-Inpainting
•
Video inpainting aims to fill spatio-temporal holes with plausible content in a video.
IMAGE INPAINTING VIDEO DENOISING VIDEO INPAINTING VIDEO-TO-VIDEO SYNTHESIS