43 citations · 102 across the 12 of their papers we have counts for
12 papers · 1 filter
3D Geometric Shape Assembly via Efficient Point Cloud Matching
Nahyuk Lee, Juhong Min, Junha Lee +4
Learning to assemble geometric shapes into a larger target structure is a pivotal task in various practical applications. In this work, we tackle this problem by establishing local…
Classification Matters: Improving Video Action Detection with Class-Specific Attention
Jinsung Lee, Taeoh Kim, Inwoong Lee +4
Video action detection (VAD) aims to detect actors and classify their actions in a video. We figure that VAD suffers more from classification rather than localization of actors. He…
Multi-view Image Prompted Multi-view Diffusion for Improved 3D Generation
Seungwook Kim, Yichun Shi, Kejie Li +2
Using image as prompts for 3D generation demonstrate particularly strong performances compared to using text prompts alone, for images provide a more intuitive guidance for the 3D…
Learning SO(3)-Invariant Semantic Correspondence via Local Shape Transform
Chunghyun Park, Seungwook Kim, Jaesik Park +1
Establishing accurate 3D correspondences between shapes stands as a pivotal challenge with profound implications for computer vision and robotics. However, existing self-supervised…
Learning Correlation Structures for Vision Transformers
Manjin Kim, Paul Hongsuck Seo, Cordelia Schmid +1
We introduce a new attention mechanism, dubbed structural self-attention (StructSA), that leverages rich correlation patterns naturally emerging in key-query interactions of attent…
Relational Context Learning for Human-Object Interaction Detection
Sanghyun Kim, Deunsol Jung, Minsu Cho
Recent state-of-the-art methods for HOI detection typically build on transformer architectures with two decoder branches, one for human-object pair detection and the other for inte…