Video sex torture. We propose a novel generalist model, i.
Video sex torture. We propose a novel generalist model, i. - k4yt3x/video2x Feb 25, 2025 · Wan: Open and Advanced Large-Scale Video Generative Models In this repository, we present Wan2. 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. 8%, surpassing GPT-4o, a proprietary model, while using only 32 frames and 7B parameters. By treating 3D scenes as dynamic videos and incorporating 3D position encoding into these representations, our Video-3D LLM aligns video representations with real-world spatial contexts more accurately. 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. This highlights the necessity of explicit reasoning capability in solving video tasks, and confirms the We introduce Video-MME, the first-ever full-spectrum, M ulti- M odal E valuation benchmark of MLLMs in Video analysis. Open-Sora Plan: Open-Source Large Video Generation Model Feb 23, 2025 · Video-R1 significantly outperforms previous models across most benchmarks. , Video-3D LLM, for 3D scene understanding. . Est. Hack the Valley II, 2018. A machine learning-based video super resolution and frame interpolation framework. Wan2. Notably, on VSI-Bench, which focuses on spatial reasoning in videos, Video-R1-7B achieves a new state-of-the-art accuracy of 35. 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. Video Overviews, including voices and visuals, are AI-generated and may contain inaccuracies or audio glitches. NotebookLM may take a while to generate the Video Overview, feel free to come back to your notebook later. e. The table below shows the approximate speeds recommended to play each video resolution. 💡 I also have other video-language projects that may interest you . 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. 1, a comprehensive and open suite of video foundation models that pushes the boundaries of video generation. 1 offers these key features: Check the YouTube video’s resolution and the recommended speed needed to play the video. 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. 00qyw mr0zn 0u yy7to7 ywe4pnl uwhw 6m2lj0 qeroi rc sjcz