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SR-Edit is proposed, an image editing framework that overcomes issues via iterative self-refinement and achieves superior preservation and overall image quality compared to existing editing techniques.
This work introduces TD-V2A, which leverages temporal differences (TD) as the key representation that distinguishes V2A from I2A, enriching visual conditioning with minimal architectural modification and significantly improves end-to-end V2A generation quality, even outperforming dedicated V2A representations such as c...
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