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- DepthAnything Video-Depth-Anything - GitHub
This work presents Video Depth Anything based on Depth Anything V2, which can be applied to arbitrarily long videos without compromising quality, consistency, or generalization ability Compared with other diffusion-based models, it enjoys faster inference speed, fewer parameters, and higher consistent depth accuracy
- GitHub - k4yt3x video2x: A machine learning-based video super . . .
A machine learning-based video super resolution and frame interpolation framework Est Hack the Valley II, 2018 - k4yt3x video2x
- Wan: Open and Advanced Large-Scale Video Generative Models
Wan: Open and Advanced Large-Scale Video Generative Models In this repository, we present Wan2 1, a comprehensive and open suite of video foundation models that pushes the boundaries of video generation Wan2 1 offers these key features:
- Video-R1: Reinforcing Video Reasoning in MLLMs - GitHub
Inspired by DeepSeek-R1's success in eliciting reasoning abilities through rule-based RL, we introduce Video-R1 as the first work to systematically explore the R1 paradigm for eliciting video reasoning within MLLMs
- Wan: Open and Advanced Large-Scale Video Generative Models
Wan: Open and Advanced Large-Scale Video Generative Models We are excited to introduce Wan2 2, a major upgrade to our foundational video models With Wan2 2, we have focused on incorporating the following innovations: 👍 Effective MoE Architecture: Wan2 2 introduces a Mixture-of-Experts (MoE) architecture into video diffusion models By separating the denoising process cross timesteps with
- hao-ai-lab FastVideo - GitHub
A unified inference and post-training framework for accelerated video generation - hao-ai-lab FastVideo
- GitHub - MeiGen-AI InfiniteTalk: Unlimited-length talking video . . .
We propose InfiniteTalk , a novel sparse-frame video dubbing framework Given an input video and audio track, InfiniteTalk synthesizes a new video with accurate lip synchronization while simultaneously aligning head movements, body posture, and facial expressions with
- VideoLLM-online: Online Video Large Language Model for Streaming Video
Online Video Streaming: Unlike previous models that serve as offline mode (querying responding to a full video), our model supports online interaction within a video stream It can proactively update responses during a stream, such as recording activity changes or helping with the next steps in real time
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