52 citations · 61 across the 5 of their papers we have counts for
5 papers
Revisiting Matching Response and Swept Feature Volumes for Wide-baseline Omnidirectional Stereo
Seungjin Jeon, Jongwoo Lim, Changhee Won
In this paper, we propose a training strategy for confidence estimation in omnidirectional stereo, targeting the ambiguous matches that frequently occur in wide-baseline setups. Re…
TSDF-Sampling: Efficient Sampling for Neural Surface Field using Truncated Signed Distance Field
Chaerin Min, Sehyun Cha, Changhee Won +1
Multi-view neural surface reconstruction has exhibited impressive results. However, a notable limitation is the prohibitively slow inference time when compared to traditional techn…
OmniSLAM: Omnidirectional Localization and Dense Mapping for Wide-baseline Multi-camera Systems
Changhee Won, Hochang Seok, Zhaopeng Cui +2
In this paper, we present an omnidirectional localization and dense mapping system for a wide-baseline multiview stereo setup with ultra-wide field-of-view (FOV) fisheye cameras, w…
OmniMVS: End-to-End Learning for Omnidirectional Stereo Matching
Changhee Won, Jongbin Ryu, Jongwoo Lim
In this paper, we propose a novel end-to-end deep neural network model for omnidirectional depth estimation from a wide-baseline multi-view stereo setup. The images captured with u…
SweepNet: Wide-baseline Omnidirectional Depth Estimation
Changhee Won, Jongbin Ryu, Jongwoo Lim
Omnidirectional depth sensing has its advantage over the conventional stereo systems since it enables us to recognize the objects of interest in all directions without any blind re…