1.2k citations · 1.4k across the 13 of their papers we have counts for
14 papers · 1 filter
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…
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…
Self-Supervised Real-time Video Stabilization
Jinsoo Choi, Jaesik Park, In So Kweon
Videos are a popular media form, where online video streaming has recently gathered much popularity. In this work, we propose a novel method of real-time video stabilization - tran…
Deep Point Cloud Reconstruction
Jaesung Choe, Byeongin Joung, Francois Rameau +2
Point cloud obtained from 3D scanning is often sparse, noisy, and irregular. To cope with these issues, recent studies have been separately conducted to densify, denoise, and compl…
PointMixer: MLP-Mixer for Point Cloud Understanding
Jaesung Choe, Chunghyun Park, Francois Rameau +2
MLP-Mixer has newly appeared as a new challenger against the realm of CNNs and transformer. Despite its simplicity compared to transformer, the concept of channel-mixing MLPs and t…
ContraGAN: Contrastive Learning for Conditional Image Generation
Minguk Kang, Jaesik Park
Conditional image generation is the task of generating diverse images using class label information. Although many conditional Generative Adversarial Networks (GAN) have shown real…
High-dimensional Convolutional Networks for Geometric Pattern Recognition
Christopher Choy, Junha Lee, Rene Ranftl +2
Many problems in science and engineering can be formulated in terms of geometric patterns in high-dimensional spaces. We present high-dimensional convolutional networks (ConvNets)…
Future Video Synthesis with Object Motion Prediction
Yue Wu, Rongrong Gao, Jaesik Park +1
We present an approach to predict future video frames given a sequence of continuous video frames in the past. Instead of synthesizing images directly, our approach is designed to…
Combinatorial 3D Shape Generation via Sequential Assembly
Jungtaek Kim, Hyunsoo Chung, Jinhwi Lee +2
Sequential assembly with geometric primitives has drawn attention in robotics and 3D vision since it yields a practical blueprint to construct a target shape. However, due to its c…
HUMBI: A Large Multiview Dataset of Human Body Expressions
Zhixuan Yu, Jae Shin Yoon, In Kyu Lee +4
This paper presents a new large multiview dataset called HUMBI for human body expressions with natural clothing. The goal of HUMBI is to facilitate modeling view-specific appearanc…
Tangent Convolutions for Dense Prediction in 3D
Maxim Tatarchenko, Jaesik Park, Vladlen Koltun +1
We present an approach to semantic scene analysis using deep convolutional networks. Our approach is based on tangent convolutions - a new construction for convolutional networks o…
Open3D: A Modern Library for 3D Data Processing
Qian-Yi Zhou, Jaesik Park, Vladlen Koltun
Open3D is an open-source library that supports rapid development of software that deals with 3D data. The Open3D frontend exposes a set of carefully selected data structures and al…
Refining Geometry from Depth Sensors using IR Shading Images
Gyeongmin Choe, Jaesik Park, Yu-Wing Tai +1
We propose a method to refine geometry of 3D meshes from a consumer level depth camera, e.g. Kinect, by exploiting shading cues captured from an infrared (IR) camera. A major benef…
Vision System and Depth Processing for DRC-HUBO+
Inwook Shim, Seunghak Shin, Yunsu Bok +6
This paper presents a vision system and a depth processing algorithm for DRC-HUBO+, the winner of the DRC finals 2015. Our system is designed to reliably capture 3D information of…