NVlabs/few-shot-vid2vid
A PyTorch implementation of a few-shot neural network for photorealistic video-to-video translation that generates human motions from poses and synthesizes talking head videos.
Not currently ranked — collecting fresh signals.
star history
This repository provides a deep learning model for few-shot video-to-video synthesis using PyTorch. The system can translate semantic label maps, pose sequences, and edge maps into photorealistic videos. It leverages image-to-image translation techniques and was published as a NeurIPS 2019 paper by NVIDIA researchers.
Frequently asked
- What is NVlabs/few-shot-vid2vid?
- A PyTorch implementation of a few-shot neural network for photorealistic video-to-video translation that generates human motions from poses and synthesizes talking head videos.
- Is few-shot-vid2vid open source?
- Yes — NVlabs/few-shot-vid2vid is an open-source project tracked on heatdrop.
- What language is few-shot-vid2vid written in?
- NVlabs/few-shot-vid2vid is primarily written in Python.
- How popular is few-shot-vid2vid?
- NVlabs/few-shot-vid2vid has 1.8k stars on GitHub.
- Where can I find few-shot-vid2vid?
- NVlabs/few-shot-vid2vid is on GitHub at https://github.com/NVlabs/few-shot-vid2vid.