activity
20172021
most citedDeepGMR: Learning Latent Gaussian Mixture Models for Registration

17 citations · 28 across the 5 of their papers we have counts for

collaborators

12 papers

cs.CV20215 cited

Neural 3D Clothes Retargeting from a Single Image

Jae Shin Yoon, Kihwan Kim, Jan Kautz +1

In this paper, we present a method of clothes retargeting; generating the potential poses and deformations of a given 3D clothing template model to fit onto a person in a single RG…

cs.CV202017 cited

DeepGMR: Learning Latent Gaussian Mixture Models for Registration

Wentao Yuan, Ben Eckart, Kihwan Kim +3

Point cloud registration is a fundamental problem in 3D computer vision, graphics and robotics. For the last few decades, existing registration algorithms have struggled in situati…

cs.CV2020

Novel View Synthesis of Dynamic Scenes with Globally Coherent Depths from a Monocular Camera

Jae Shin Yoon, Kihwan Kim, Orazio Gallo +2

This paper presents a new method to synthesize an image from arbitrary views and times given a collection of images of a dynamic scene. A key challenge for the novel view synthesis…

cs.CV2019

NRMVS: Non-Rigid Multi-View Stereo

Matthias Innmann, Kihwan Kim, Jinwei Gu +4

Scene reconstruction from unorganized RGB images is an important task in many computer vision applications. Multi-view Stereo (MVS) is a common solution in photogrammetry applicati…

cs.CV2019

Neural RGB->D Sensing: Depth and Uncertainty from a Video Camera

Chao Liu, Jinwei Gu, Kihwan Kim +2

Depth sensing is crucial for 3D reconstruction and scene understanding. Active depth sensors provide dense metric measurements, but often suffer from limitations such as restricted…

cs.CV20196 cited

PlaneRCNN: 3D Plane Detection and Reconstruction from a Single Image

Chen Liu, Kihwan Kim, Jinwei Gu +2

This paper proposes a deep neural architecture, PlaneRCNN, that detects and reconstructs piecewise planar surfaces from a single RGB image. PlaneRCNN employs a variant of Mask R-CN…