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cs.CV2026
Unlocking the Potential of Image Editing via Concept Scaling and Dense Supervision
Long Cui, Xiaoqian Liu, Qi Qin +4
Existing image editing frameworks predominantly follow the training paradigm of text-to-image diffusion models. However, extending this paradigm to image editing highlights two inh…
cs.CV2026
AvatarForcing: One-Step Streaming Talking Avatars via Local-Future Sliding-Window Denoising
Liyuan Cui, Wentao Hu, Wenyuan Zhang +3
Real-time talking avatar generation requires low latency and minute-level temporal stability. Autoregressive (AR) forcing enables streaming inference but suffers from exposure bias…