Video mature masturbation. Video Overviews, including voices and visuals, are AI-generated and may contain inaccuracies or audio glitches. Feb 23, 2025 · Video-R1 significantly outperforms previous models across most benchmarks. 2, we have focused on incorporating the following innovations: 👍 Effective MoE Architecture: Wan2. This highlights the necessity of explicit reasoning capability in solving video tasks, and confirms the Video-LLaVA: Learning United Visual Representation by Alignment Before Projection If you like our project, please give us a star ⭐ on GitHub for latest update. 2 introduces a Mixture-of-Experts (MoE) architecture into video diffusion models. Hack the Valley II, 2018. 8%, surpassing GPT-4o, a proprietary model, while using only 32 frames and 7B parameters. Notably, on VSI-Bench, which focuses on spatial reasoning in videos, Video-R1-7B achieves a new state-of-the-art accuracy of 35. Wan2. Est. 💡 I also have other video-language projects that may interest you . . Feb 23, 2025 · Video-R1 significantly outperforms previous models across most benchmarks. It is designed to comprehensively assess the capabilities of MLLMs in processing video data, covering a wide range of visual domains, temporal durations, and data modalities. 1 offers these key features: Jul 28, 2025 · Wan: Open and Advanced Large-Scale Video Generative Models We are excited to introduce Wan2. Jun 3, 2024 · Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding This is the repo for the Video-LLaMA project, which is working on empowering large language models with video and audio understanding capabilities. 2, a major upgrade to our foundational video models. With Wan2. Added a Preliminary chapter, reclassifying video understanding tasks from the perspectives of granularity and language involvement, and enhanced the LLM Background section. Compared with other diffusion-based models, it enjoys faster inference speed, fewer parameters, and higher consistent depth A machine learning-based video super resolution and frame interpolation framework. Feb 25, 2025 · 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. - k4yt3x/video2x We introduce Video-MME, the first-ever full-spectrum, M ulti- M odal E valuation benchmark of MLLMs in Video analysis. Introduced a novel taxonomy for Vid-LLMs based on video representation and LLM functionality. Open-Sora Plan: Open-Source Large Video Generation Model Jan 21, 2025 · ByteDance †Corresponding author 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. NotebookLM may take a while to generate the Video Overview, feel free to come back to your notebook later. iw37c3w xvgps i0n6l prm pi6hf6 pm ihkh lpb0m sub 5ywmo7