Video which make you orgasm. NotebookLM may take a while to generate the Video Overview, feel free to come back to your notebook later. Hack the Valley II, 2018. 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. 8%, surpassing GPT-4o, a proprietary model, while using only 32 frames and 7B parameters. Video Overviews, including voices and visuals, are AI-generated and may contain inaccuracies or audio glitches. Compared with other diffusion-based models, it enjoys faster inference speed, fewer parameters, and higher consistent depth 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. - k4yt3x/video2x We introduce Video-MME, the first-ever full-spectrum, M ulti- M odal E valuation benchmark of MLLMs in Video analysis. Wan2. Jul 28, 2025 · Wan: Open and Advanced Large-Scale Video Generative Models We are excited to introduce Wan2. Est. Added a Preliminary chapter, reclassifying video understanding tasks from the perspectives of granularity and language involvement, and enhanced the LLM Background section. 1, a comprehensive and open suite of video foundation models that pushes the boundaries of video generation. 1 offers these key features: With the Google Meet app, you can: Create or join scheduled or instant cloud-encrypted Google Meet meetings with a link. This highlights the necessity of explicit reasoning capability in solving video tasks, and confirms the Feb 25, 2025 · Wan: Open and Advanced Large-Scale Video Generative Models In this repository, we present Wan2. Ring directly to a Google Workspace, personal account, or phone number. 2, we have focused on incorporating the following innovations: 👍 Effective MoE Architecture: Wan2. Introduced a novel taxonomy for Vid-LLMs based on video representation and LLM functionality. 2, a major upgrade to our foundational video models. Notably, on VSI-Bench, which focuses on spatial reasoning in videos, Video-R1-7B achieves a new state-of-the-art accuracy of 35. A machine learning-based video super resolution and frame interpolation framework. . 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. With Wan2. 2 introduces a Mixture-of-Experts (MoE) architecture into video diffusion models. 💡 I also have other video-language projects that may interest you . Open-Sora Plan: Open-Source Large Video Generation Model Feb 23, 2025 · Video-R1 significantly outperforms previous models across most benchmarks. 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.