video full hadeer abdelrazik video فيديو هدير عبد الرازق الجديد كاملو c

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 Jun 24, 2025 OmniAvatar: Efficient Audio-Driven Avatar Video Generation with Adaptive Body Animation Qijun Gan Ruizi Yang Jianke Zhu Shaofei Xue Steven Hoi Zhejiang University, Alibaba Group Jan 21, 2025 VideoLLaMA 3 is a series of multimodal foundation models with frontier image and video understanding capacity. Click here to show detailed performance on video benchmarks Feb 15, 2025 Solve Visual Understanding with Reinforced VLMs. Contribute to om-ai-lab/VLM-R1 development by creating an account on GitHub. Mar 17, 2025 GCD: GCD synthesizes large-angle novel viewpoints of 4D dynamic scenes from a monocular video. ReCapture: a method for generating new videos with novel camera trajectories from a single user-provided video. Trajectory Attention: Trajectory Attention facilitates various tasks like camera motion control on images and videos, and video editing. yt-dlp is a feature-rich command-line audio/video downloader with support for thousands of sites. The project is a fork of youtube-dl based on the now inactive youtube-dlc. INSTALLATION Detailed instructions Release Files Update Dependencies Compile USAGE AND OPTIONS General Options Network Options Geo-restriction Video Selection Download Options Qwen2.5-VL is the multimodal large language model series developed by Qwen team, Alibaba Cloud. - QwenLM/Qwen2.5-VL [WIP] The all in one inference optimization solution for ComfyUI, universal, flexible, and fast. - chengzeyi/Comfy-WaveSpeed Grounded SAM 2 Video Object Tracking Demo with Custom Video Input (with Grounding DINO 1.5 & 1.6)

Users can upload their own video file (e.g. assets/hippopotamus.mp4) and specify their custom text prompts for grounding and tracking with Grounding DINO 1.5 and SAM 2 by using the following scripts: Pusa (pu: 'sA:, from "Thousand-Hand Guanyin" in Chinese) introduces a paradigm shift in video diffusion modeling through frame-level noise control with vectorized timesteps, departing from conventional scalar timestep approaches.