Robotics · Computer Science
LiStereo: Generate Dense Depth Maps from LIDAR and Stereo Imagery
Junming Zhang, Manikandasriram Srinivasan Ramanagopal, Ram Vasudevan, Matthew Johnson-Roberson
2020-06-29
Computer Vision and Pattern Recognition · Computer Science
Robust and accurate depth estimation by fusing LiDAR and Stereo
Guangyao Xu, Junfeng Fan, En Li, Xiaoyu Long +1
2023-08-24
Computer Vision and Pattern Recognition · Computer Science
Depth Refinement for Improved Stereo Reconstruction
Amit Bracha, Noam Rotstein, David Bensaïd, Ron Slossberg +1
2021-12-16
Computer Vision and Pattern Recognition · Computer Science
Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving
Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan +2
2020-02-25
Computer Vision and Pattern Recognition · Computer Science
A Survey on Deep Learning Techniques for Stereo-based Depth Estimation
Hamid Laga, Laurent Valentin Jospin, Farid Boussaid, Mohammed Bennamoun
2021-01-26
Computer Vision and Pattern Recognition · Computer Science
Learning Pseudo Front Depth for 2D Forward-Looking Sonar-based Multi-view Stereo
Yusheng Wang, Yonghoon Ji, Hiroshi Tsuchiya, Hajime Asama +1
2022-08-02
Computer Vision and Pattern Recognition · Computer Science
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving
Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg +4
2020-02-18
Computer Vision and Pattern Recognition · Computer Science
Normal Assisted Stereo Depth Estimation
Uday Kusupati, Shuo Cheng, Rui Chen, Hao Su
2020-06-02
Computer Vision and Pattern Recognition · Computer Science
LiDAR-Flow: Dense Scene Flow Estimation from Sparse LiDAR and Stereo Images
Ramy Battrawy, René Schuster, Oliver Wasenmüller, Qing Rao +1
2019-12-16
Computer Vision and Pattern Recognition · Computer Science
Accurate and Real-time Pseudo Lidar Detection: Is Stereo Neural Network Really Necessary?
Haitao Meng, Changcai Li, Gang Chen, Alois Knoll
2022-06-29
Computer Vision and Pattern Recognition · Computer Science
Sparse LiDAR Assisted Self-supervised Stereo Disparity Estimation
Xiaoming Zhao, Weihai Chen, Xingming Wu, Peter C. Y. Chen +1
2022-01-03
Computer Vision and Pattern Recognition · Computer Science
Bi3D: Stereo Depth Estimation via Binary Classifications
Abhishek Badki, Alejandro Troccoli, Kihwan Kim, Jan Kautz +2
2020-06-02
Computer Vision and Pattern Recognition · Computer Science
Real Time Dense Depth Estimation by Fusing Stereo with Sparse Depth Measurements
Shreyas S. Shivakumar, Kartik Mohta, Bernd Pfrommer, Vijay Kumar +1
2018-09-21
Computer Vision and Pattern Recognition · Computer Science
Self-Supervised Depth Completion for Active Stereo
Frederik Warburg, Daniel Hernandez-Juarez, Juan Tarrio, Alexander Vakhitov +2
2022-01-21
Computer Vision and Pattern Recognition · Computer Science
Du$^2$Net: Learning Depth Estimation from Dual-Cameras and Dual-Pixels
Yinda Zhang, Neal Wadhwa, Sergio Orts-Escolano, Christian Häne +2
2020-04-01
Computer Vision and Pattern Recognition · Computer Science
Self-Supervised Depth Estimation in Laparoscopic Image using 3D Geometric Consistency
Baoru Huang, Jian-Qing Zheng, Anh Nguyen, Chi Xu +5
2023-06-22
Computer Vision and Pattern Recognition · Computer Science
3D LiDAR and Stereo Fusion using Stereo Matching Network with Conditional Cost Volume Normalization
Tsun-Hsuan Wang, Hou-Ning Hu, Chieh Hubert Lin, Yi-Hsuan Tsai +2
2019-04-08
Computer Vision and Pattern Recognition · Computer Science
Stereo-LiDAR Fusion by Semi-Global Matching With Discrete Disparity-Matching Cost and Semidensification
Yasuhiro Yao, Ryoichi Ishikawa, Takeshi Oishi
2025-04-08
Computer Vision and Pattern Recognition · Computer Science
Edge-aware Consistent Stereo Video Depth Estimation
Elena Kosheleva, Sunil Jaiswal, Faranak Shamsafar, Noshaba Cheema +2
2023-05-05
Computer Vision and Pattern Recognition · Computer Science
Stereo-LiDAR Depth Estimation with Deformable Propagation and Learned Disparity-Depth Conversion
Ang Li, Anning Hu, Wei Xi, Wenxian Yu +1
2024-04-12
Computer Vision and Pattern Recognition · Computer Science
On the confidence of stereo matching in a deep-learning era: a quantitative evaluation
Matteo Poggi, Seungryong Kim, Fabio Tosi, Sunok Kim +4
2021-04-01