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cs.CV2025
Edit2Perceive: Image Editing Diffusion Models Are Strong Dense Perceivers
Yiqing Shi, Yiren Song, Mike Zheng Shou
Recent advances in diffusion transformers have shown remarkable generalization in visual synthesis, yet most dense perception methods still rely on text-to-image (T2I) generators d…
cs.CV2025
InstructUDrag: Joint Text Instructions and Object Dragging for Interactive Image Editing
Haoran Yu, Yi Shi
Text-to-image diffusion models have shown great potential for image editing, with techniques such as text-based and object-dragging methods emerging as key approaches. However, eac…
cs.CV2025
StableMotion: Training Motion Cleanup Models with Unpaired Corrupted Data
Yuxuan Mu, Hung Yu Ling, Yi Shi +5
Motion capture (mocap) data often exhibits visually jarring artifacts due to inaccurate sensors and post-processing. Cleaning this corrupted data can require substantial manual eff…