18 citations · 74 across the 21 of their papers we have counts for
12 papers · 1 filter
Fast Point Transformer
Chunghyun Park, Yoonwoo Jeong, Minsu Cho +1
The recent success of neural networks enables a better interpretation of 3D point clouds, but processing a large-scale 3D scene remains a challenging problem. Most current approach…
Revisiting LiDAR Registration and Reconstruction: A Range Image Perspective
Wei Dong, Kwonyoung Ryu, Michael Kaess +1
Spinning LiDAR data are prevalent for 3D vision tasks. Since LiDAR data is presented in the form of point clouds, expensive 3D operations are usually required. This paper revisits…
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…
Instance-wise Occlusion and Depth Orders in Natural Scenes
Hyunmin Lee, Jaesik Park
In this paper, we introduce a new dataset, named InstaOrder, that can be used to understand the geometrical relationships of instances in an image. The dataset consists of 2.9M ann…
Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training
Minguk Kang, Woohyeon Shim, Minsu Cho +1
Conditional Generative Adversarial Networks (cGAN) generate realistic images by incorporating class information into GAN. While one of the most popular cGANs is an auxiliary classi…
Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning
Hyunsoo Chung, Jungtaek Kim, Boris Knyazev +4
Discovering a solution in a combinatorial space is prevalent in many real-world problems but it is also challenging due to diverse complex constraints and the vast number of possib…
HUMBI: A Large Multiview Dataset of Human Body Expressions and Benchmark Challenge
Jae Shin Yoon, Zhixuan Yu, Jaesik Park +1
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…
Deep Hough Voting for Robust Global Registration
Junha Lee, Seungwook Kim, Minsu Cho +1
Point cloud registration is the task of estimating the rigid transformation that aligns a pair of point cloud fragments. We present an efficient and robust framework for pairwise r…
Self-Calibrating Neural Radiance Fields
Yoonwoo Jeong, Seokjun Ahn, Christopher Choy +3
In this work, we propose a camera self-calibration algorithm for generic cameras with arbitrary non-linear distortions. We jointly learn the geometry of the scene and the accurate…
Realistic Image Synthesis with Configurable 3D Scene Layouts
Jaebong Jeong, Janghun Jo, Jingdong Wang +2
Recent conditional image synthesis approaches provide high-quality synthesized images. However, it is still challenging to accurately adjust image contents such as the positions an…
Spatiotemporal Texture Reconstruction for Dynamic Objects Using a Single RGB-D Camera
Hyomin Kim, Jungeon Kim, Hyeonseo Nam +2
This paper presents an effective method for generating a spatiotemporal (time-varying) texture map for a dynamic object using a single RGB-D camera. The input of our framework is a…
Deep Virtual Markers for Articulated 3D Shapes
Hyomin Kim, Jungeon Kim, Jaewon Kam +2
We propose deep virtual markers, a framework for estimating dense and accurate positional information for various types of 3D data. We design a concept and construct a framework th…