2 citations · 2 across the 4 of their papers we have counts for
6 papers
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…
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…
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…
Metropolis-Hastings Sampling for 3D Gaussian Reconstruction
Hyunjin Kim, Haebeom Jung, Jaesik Park
We propose an adaptive sampling framework for 3D Gaussian Splatting (3DGS) that leverages comprehensive multi-view photometric error signals within a unified Metropolis-Hastings ap…
Visual Acoustic Fields
Yuelei Li, Hyunjin Kim, Fangneng Zhan +7
Objects produce different sounds when hit, and humans can intuitively infer how an object might sound based on its appearance and material properties. Inspired by this intuition, w…
Toward Reinforcement Learning-based Rectilinear Macro Placement Under Human Constraints
Tuyen P. Le, Hieu T. Nguyen, Seungyeol Baek +8
Macro placement is a critical phase in chip design, which becomes more intricate when involving general rectilinear macros and layout areas. Furthermore, macro placement that incor…