VisoMaster is a powerful yet easy-to-use tool for face swapping and editing in images and videos. It utilizes AI to produce natural-looking results with minimal effort, making it ideal for both casual users and professionals. Jul 28, 2025 · Wan: Open and Advanced Large-Scale Video Generative Models We are excited to introduce Wan2.2, a major upgrade to our foundational video models. With Wan2.2, we have focused on incorporating the following innovations: 👍 Effective MoE Architecture: Wan2.2 introduces a Mixture-of-Experts (MoE) architecture into video diffusion models. By separating the denoising process cross timesteps with A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018. - k4yt3x/video2x Accessories and hardware kits for Meet Set up Meet to help your team work remotely Accessibility in Google Meet Get the new Meet app in the play store or app store Google Meet is your one app for video calling and meetings across all devices. Use video calling features like fun filters and effects or schedule time to connect when everyone can join. 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. 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 Filesystem Options Thumbnail Options Internet Jan 21, 2025 · 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 LTX-Video is the first DiT-based video generation model that can generate high-quality videos in real-time. It can generate 30 FPS videos at 1216×704 resolution, faster than it takes to watch them. The model is trained on a large-scale dataset of diverse videos and can generate high-resolution videos with realistic and diverse content. The model supports image-to-video, keyframe-based MAGREF: Masked Guidance for Any-Reference Video Generation 🔥 News [2025.06.20] 🙏 Thanks to Kijai for developing the ComfyUI nodes for MAGREF and FP8-quantized Hugging Face mode! Feel free to try them out and add MAGREF to your workflow. [2025.06.18] 🔥 In progress. Guidelines for video creatives Check YouTube videos in YouTube & partners line items for guidelines on YouTube videos in YouTube & partners line items. The guidelines in this article don’t apply to YouTube videos for YouTube & partners line items. For guidelines on display ads with embedded video players, check the Guidelines for in-banner video.