Upscale-A-Video
U
Upscale A Video
Overview :
Upscale-A-Video is a diffusion-based model designed to increase video resolution by taking low-resolution videos and text prompts as input. The model ensures temporal consistency through two key mechanisms: locally, it integrates temporal layers into the U-Net and VAE-Decoder to maintain consistency in short sequences; globally, it introduces a stream-guided recurrent potential propagation module that enhances overall video stability by propagating and fusing potential information throughout the sequence. Due to the diffusion paradigm, our model balances fidelity and quality by allowing text prompts to guide texture creation and tunable noise levels, thus achieving a trade-off between restoration and generation. Extensive experiments have proved that Upscale-A-Video outperforms existing methods across synthetic and real-world benchmarks as well as AI-generated videos, demonstrating impressive visual fidelity and temporal consistency.
Target Users :
Suited for scenarios that require enhancing video resolution while maintaining temporal consistency
Total Visits: 25.5K
Top Region: CN(44.48%)
Website Views : 70.1K
Use Cases
Enhance the video quality of old movie clips
Increase the resolution of real-world videos
Enhance the visual quality of animated videos
Features
Process long videos through local and global strategies to maintain temporal consistency
Use U-Net and temporal layers to process video segments to achieve segment consistency
Utilize the recurrent potential propagation module to enhance inter-segment consistency
Reduce remaining flicker artifacts with a fine-tuned VAE-Decoder to maintain low-level consistency
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