14 citations · 27 across the 8 of their papers we have counts for
8 papers
Fill-Up: Balancing Long-Tailed Data with Generative Models
Joonghyuk Shin, Minguk Kang, Jaesik Park
Modern text-to-image synthesis models have achieved an exceptional level of photorealism, generating high-quality images from arbitrary text descriptions. In light of the impressiv…
Instant Domain Augmentation for LiDAR Semantic Segmentation
Kwonyoung Ryu, Soonmin Hwang, Jaesik Park
Despite the increasing popularity of LiDAR sensors, perception algorithms using 3D LiDAR data struggle with the 'sensor-bias problem'. Specifically, the performance of perception a…
LaplacianFusion: Detailed 3D Clothed-Human Body Reconstruction
Hyomin Kim, Hyeonseo Nam, Jungeon Kim +2
We propose LaplacianFusion, a novel approach that reconstructs detailed and controllable 3D clothed-human body shapes from an input depth or 3D point cloud sequence. The key idea o…
Style-Agnostic Reinforcement Learning
Juyong Lee, Seokjun Ahn, Jaesik Park
We present a novel method of learning style-agnostic representation using both style transfer and adversarial learning in the reinforcement learning framework. The style, here, ref…
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…