When exploring video game character concept art, it's essential to consider various aspects and implications. 【EMNLP 2024 】Video-LLaVA: Learning United Visual ... 😮 Highlights Video-LLaVA exhibits remarkable interactive capabilities between images and videos, despite the absence of image-video pairs in the dataset. DepthAnything/Video-Depth-Anything - GitHub.
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 ... GitHub - k4yt3x/video2x: A machine learning-based video super .... Similarly, a machine learning-based video super resolution and frame interpolation framework. Hack the Valley II, 2018. 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. Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video .... Similarly, wan: Open and Advanced Large-Scale Video Generative Models.
Wan2.1 offers these key features: Generate Video Overviews in NotebookLM - Google Help. This perspective suggests that, 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. Video-R1: Reinforcing Video Reasoning in MLLMs - GitHub.
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. In relation to this, this highlights the necessity of explicit reasoning capability in solving video tasks, and confirms the ... GitHub - meituan-longcat/LongCat-Video. We introduce LongCat-Video, a foundational video generation model with 13.6B parameters, delivering strong performance across Text-to-Video, Image-to-Video, and Video-Continuation generation tasks.
It particularly excels in efficient and high-quality long video generation, representing our first step toward world models. From another angle, frontier Multimodal Foundation Models for Image and Video ... 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
📝 Summary
As demonstrated, video game character concept art constitutes a valuable field that deserves consideration. Going forward, additional research on this topic will deliver more comprehensive knowledge and advantages.