Awesome-Video-Diffusion and awesome-diffusion-v2v
These are complementary resources where one provides a broad survey of video diffusion models across multiple tasks, while the other offers a specialized, deeper focus on the video-to-video editing subset with benchmark implementations.
About Awesome-Video-Diffusion
showlab/Awesome-Video-Diffusion
A curated list of recent diffusion models for video generation, editing, and various other applications.
This is a curated list of tools and resources for generating and editing videos using AI. It helps video creators, marketers, and content producers find different methods to create videos from scratch, modify existing footage, or enhance video quality. You can input text, images, or existing video clips to generate new scenes, apply artistic styles, or restore old videos.
About awesome-diffusion-v2v
wenhao728/awesome-diffusion-v2v
Awesome diffusion Video-to-Video (V2V). A collection of paper on diffusion model-based video editing, aka. video-to-video (V2V) translation. And a video editing benchmark code.
This is a curated collection of cutting-edge research papers and a benchmark for video editing using advanced AI models. It helps video creators and researchers understand and apply techniques that transform existing video footage based on specific instructions. You can input a video and an editing goal, and learn about methods to produce a modified video, allowing for sophisticated visual changes.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work