AI paper index
Making Time Editable in Video Diffusion Transformers
One-line summary
An AI research paper on Making Time Editable in Video Diffusion Transformers.
Engineering notes
Engineering notes will be added by the aipentium editorial team.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为大语言模型、生成式AI、ChatGPT相关技术、计算机视觉、深度学习等高价值论文补充中文说明。
Original abstract
Modern Diffusion Transformers for video generation provide limited control over the progression of time and the editing of temporal dynamics. We propose a temporal-control methodology that extends a pretrained DiT with explicit time editing, allowing control over motion speed and temporal structure without redesigning the backbone. Its core implementation augments the pretrained model with a lightweight temporal module, preserving the original generative prior while expanding its controllable dynamic range.
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