Pixel diffusion models generate RGB images directly, avoiding the bottleneck of an autoencoder, yet their outputs still systematically underrepresent fine-scale natural-image statistics. We show that adversarial learning provides an effective post-training correction for this deficiency. Starting from a pretrained mode...
Xin Lin, Zhi-Fei Zhang, Yu-Qian Zhou et al.· 0 citations
Recent generative video editing models enable video content modification (e.g., changing a character) but target short clips. Extending them to full multi-shot videos requires tedious work to locate relevant content across shots, segment it into clips, craft context-aware editing prompts for each clip, and repeatedly a...
Boyu Li, Yu-Qian Zhou, Duo-Tun Wang et al.· 0 citations
Interactive video generation and editing are becoming increasingly important for creative design. In this report, we introduce EditStream: a unified framework for interactive video generation and editing. EditStream unifies multiple video creation and manipulation tasks within a single DiT-based model through flexible...
Yu-Qian Zhou, Zhenghong Zhou, Zongze Wu et al.· 0 citations
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