AI RESEARCH
SEDiT: Mask-Free Video Subtitle Erasure via One-step Diffusion Transformer
arXiv CS.CV
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ArXi:2605.14894v1 Announce Type: new Recent breakthroughs in video diffusion models have significantly accelerated the development of video editing techniques. However, existing methods often rely on inpainting video frames based on masked input, which requires extracting the target video mask in advance, and the precision of the segmentation directly affects the quality of the completion. In this paper, we present SEDiT, a novel one-stage video Subtitle Erasure approach via One-step Diffusion Transformer. We