6 citations · 7 across the 3 of their papers we have counts for
4 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…
PeRFception: Perception using Radiance Fields
Yoonwoo Jeong, Seungjoo Shin, Junha Lee +4
The recent progress in implicit 3D representation, i.e., Neural Radiance Fields (NeRFs), has made accurate and photorealistic 3D reconstruction possible in a differentiable manner.…
Learning to Register Unbalanced Point Pairs
Kanghee Lee, Junha Lee, Jaesik Park
Point cloud registration methods can effectively handle large-scale, partially overlapping point cloud pairs. Despite its practicality, matching the unbalanced pairs in terms of sp…
Putting 3D Spatially Sparse Networks on a Diet
Junha Lee, Christopher Choy, Jaesik Park
3D neural networks have become prevalent for many 3D vision tasks including object detection, segmentation, registration, and various perception tasks for 3D inputs. However, due t…