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. Compared with other diffusion-based models, it enjoys faster inference speed, fewer parameters, and higher consistent depth Feb 23, 2025 · Video-R1 significantly outperforms previous models across most benchmarks. Notably, on VSI-Bench, which focuses on spatial reasoning in videos, Video-R1-7B achieves a new state-of-the-art accuracy of 35.8%, surpassing GPT-4o, a proprietary model, while using only 32 frames and 7B parameters. 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. 💡 I also have other video-language projects that may interest you . Open-Sora Plan: Open-Source Large Video Generation Model Check the YouTube video’s resolution and the recommended speed needed to play the video. The table below shows the approximate speeds recommended to play each video resolution. We introduce Video-MME, the first-ever full-spectrum, M ulti- M odal E valuation benchmark of MLLMs in Video analysis. 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. 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. Wan2.1 offers these key features: 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. A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018. - k4yt3x/video2x 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. Introduced a novel taxonomy for Vid-LLMs based on video representation and LLM functionality. Added a Preliminary chapter, reclassifying video understanding tasks from the perspectives of granularity and language involvement, and enhanced the LLM Background section. This Telegram bot allows you to download videos from YouTube and other supported websites.  Specific link downloader (Use /spdl for these links). Instagram (Videos, Photos, Reels, IGTV & carousel). Python-telegram-bot: A Telegram wrapper in Python. Decouple: A Python library to store parameters in .env files. youtube-dl: A Command-line program to download videos from YouTube. You can install them in the virtual environment using pip command. Download videos from YouTube and TT Chief: @alexmboss. Start Bot. If you have Telegram, you can launch YoutubeDL - YouTube Download Bot right away. Just paste the youtube link and get the video in any quality.  If you have Telegram, you can view and join HD YouTube Video Downloader right away. Pyrogram YouTube Downloader Bot.  To use the bot, simply start a chat with it on Telegram and enter a valid YouTube video or playlist URL. Our Telegram bot allows you to easily download videos from popular platforms: YouTube, TikTok, RuTube, VKontakte, and Odnoklassniki. Telegram Bot Youtube Downloader. The bot requests getInfo video from youtube-dl and gives URLs for downloading. Installation. With npm do python telegram_video_downloader.py. Open Telegram and search for the name of your bot. Start a chat with your bot, and send it a YouTube video URL. Convert Videos to round Video

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