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- DepthAnything Video-Depth-Anything - GitHub
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 accuracy
- Troubleshoot YouTube video errors - Google Help
Run an Internet speed test to make sure that your Internet can support the selected video resolution Using multiple devices on the same network may reduce the speed that your device gets You can also change the quality of your video to improve your experience Check the YouTube video's resolution and the recommended speed needed to play the video The table below shows the approximate speeds
- Troubleshoot YouTube video errors - Google Help
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
- Video-R1: Reinforcing Video Reasoning in MLLMs - GitHub
Inspired by DeepSeek-R1's success in eliciting reasoning abilities through rule-based RL, we introduce Video-R1 as the first work to systematically explore the R1 paradigm for eliciting video reasoning within MLLMs
- 【EMNLP 2024 】Video-LLaVA: Learning United Visual . . . - GitHub
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
- VideoLLM-online: Online Video Large Language Model for Streaming Video
Online Video Streaming: Unlike previous models that serve as offline mode (querying responding to a full video), our model supports online interaction within a video stream It can proactively update responses during a stream, such as recording activity changes or helping with the next steps in real time
- GitHub - MME-Benchmarks Video-MME: [CVPR 2025] Video-MME: The First . . .
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
- Download the Google Meet app - Computer - Google Meet Help
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
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