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Progress in general-purpose video editing depends on constructing large-scale paired supervision and effectively adapting video-generation backbones to instruction-driven editing. Unlike video generation, video editing must execute a requested transformation while preserving unrelated subjects, scene structure, motion,...
InstructVVT is proposed, an instruction-driven and reference-guided video virtual try-on framework based on a Diffusion Transformer that operates without inference-time spatial priors that outperforms state-of-the-art open-source methods in garment fidelity, structural preservation, and temporal consistency, despite re...
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