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cs.CV2026
Vitality-Aware Compression for Efficient Image-to-Shape Diffusion Transformers
Jaeah Lee, Hyunjin Kim, Jaewoong Cho +1
We propose the first compression approach for image-to-shape Diffusion Transformers (DiTs) that substantially reduces model size while preserving geometric fidelity. Despite remark…
cs.CV2026
EgoPhys: Learning Generalizable Physics Models of Deformable Objects from Egocentric Video
Hyunjin Kim, Ri-Zhao Qiu, Guangqi Jiang +1
Humans naturally understand object physics through everyday interactions, but faithfully predicting complex deformable dynamics, such as elastic materials and fabrics, remains a ma…
cs.CV2026
Accelerating Diffusion via Hybrid Data-Pipeline Parallelism Based on Conditional Guidance Scheduling
Euisoo Jung, Byunghyun Kim, Hyunjin Kim +2
Diffusion models have achieved remarkable progress in high-fidelity image, video, and audio generation, yet inference remains computationally expensive. Nevertheless, current diffu…