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Generation: Wan2.1 is the first video model capable of generating both Chinese and English text, featuring robust text generation that enhances its practical applications. A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018. - k4yt3x/video2x 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. 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 [2024.09.25] 🔥🔥🔥 Our Video-LLaVA has been accepted at EMNLP 2024! We earn the meta score of 4. [2024.07.27] 🔥🔥🔥 A fine-tuned Video-LLaVA focuses on theme exploration, narrative analysis, and character dynamics. May 8, 2025 · Customized video generation aims to produce videos featuring specific subjects under flexible user-defined conditions, yet existing methods often struggle with identity consistency and limited input modalities. In this paper, we propose HunyuanCustom, a multi-modal customized video generation 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 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
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