33 citations · 72 across the 16 of their papers we have counts for
4 papers · 1 filter
360SD-Net: 360° Stereo Depth Estimation with Learnable Cost Volume
Ning-Hsu Wang, Bolivar Solarte, Yi-Hsuan Tsai +2
Recently, end-to-end trainable deep neural networks have significantly improved stereo depth estimation for perspective images. However, 360° images captured under equirectangular…
Bridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence
Hsueh-Ying Lai, Yi-Hsuan Tsai, Wei-Chen Chiu
Stereo matching and flow estimation are two essential tasks for scene understanding, spatially in 3D and temporally in motion. Existing approaches have been focused on the unsuperv…
3D LiDAR and Stereo Fusion using Stereo Matching Network with Conditional Cost Volume Normalization
Tsun-Hsuan Wang, Hou-Ning Hu, Chieh Hubert Lin +3
The complementary characteristics of active and passive depth sensing techniques motivate the fusion of the Li-DAR sensor and stereo camera for improved depth perception. Instead o…
All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation
Wei-Lun Chang, Hui-Po Wang, Wen-Hsiao Peng +1
In this paper we tackle the problem of unsupervised domain adaptation for the task of semantic segmentation, where we attempt to transfer the knowledge learned upon synthetic datas…