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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. Jan 13, 2025 · We present HunyuanVideo, a novel open-source video foundation model that exhibits performance in video generation that is comparable to, if not superior to, leading closed-source models. In order to train HunyuanVideo model, we adopt several key technologies for model learning, including data We present Step-Video-T2V, a state-of-the-art (SoTA) text-to-video pre-trained model with 30 billion parameters and the capability to generate videos up to 204 frames. To enhance both training and inference efficiency, we propose a deep compression VAE for videos, achieving 16x16 spatial and 8x temporal compression ratios. 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. It can generate 30 FPS videos at 1216×704 resolution, faster than it takes to watch them. Apr 17, 2025 · FramePack is a next-frame (next-frame-section) prediction neural network structure that generates videos progressively. FramePack compresses input contexts to a constant length so that the generation workload is invariant to video length. FramePack can process a very large number of frames with 13B It features a clean, consistent API that works across popular video models, making it easier for developers to author new models and incorporate system- or kernel-level optimizations. With FastVideo's optimizations, you can achieve more than 3x inference improvement
compared to other systems A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018. - k4yt3x/video2x Sequence Conditioning – Allows motion interpolation from a given frame sequence, enabling video extension from the beginning, end, or middle of the original video. Prompt Enhancer – A new node that helps generate prompts optimized for the best model performance. See the Example Workflows section for more details.
