JOINT 3D ESTIMATION OF VEHICLES AND SCENE FLOW

96 citations as recorded by crossref.

1. SRH-Net: Stacked Recurrent Hourglass Network for Stereo Matching H. Du et al. 10.1109/LRA.2021.3101523
2. Equal Baseline Camera Array—Calibration, Testbed and Applications A. Kaczmarek & B. Blaschitz 10.3390/app11188464
3. Motion Decoupling Network for Intra-Operative Motion Estimation Under Occlusion G. Bian et al. 10.1109/TMI.2023.3268774
4. 3D Point-Voxel Correlation Fields for Scene Flow Estimation Z. Wang et al. 10.1109/TPAMI.2023.3294355
5. Stereo matching on images based on volume fusion and disparity space attention L. Liao et al. 10.1016/j.engappai.2024.108902
6. FPGA-based stereo matching for crop height measurement using monocular camera I. Firmansyah et al. 10.1016/j.micpro.2024.105063
7. OmniGlasses: an optical aid for stereo vision CNNs to enable omnidirectional image processing J. Seuffert et al. 10.1007/s00138-024-01534-2
8. STFlow: Self-Taught Optical Flow Estimation Using Pseudo Labels Z. Ren et al. 10.1109/TIP.2020.3024015
9. Revisiting Dead Leaves Model: Training With Synthetic Data P. Madhusudana et al. 10.1109/LSP.2021.3132289
10. Information from imagery: ISPRS scientific vision and research agenda J. Chen et al. 10.1016/j.isprsjprs.2015.09.008
11. SemFlow: Semantic-Driven Interpolation for Large Displacement Optical Flow X. Wang et al. 10.1109/ACCESS.2019.2911021
12. Efficient Stereo Depth Estimation for Pseudo-LiDAR: A Self-Supervised Approach Based on Multi-Input ResNet Encoder S. Hossain & X. Lin 10.3390/s23031650
13. SDF-MAN: Semi-Supervised Disparity Fusion with Multi-Scale Adversarial Networks C. Pu et al. 10.3390/rs11050487
14. GFANet: Group Fusion Aggregation Network for Real Time Stereo Matching Y. Zhang & J. Zhang 10.1109/LRA.2023.3280818
15. Learning Efficient Stereo Matching Network With Depth Discontinuity Aware Super-Resolution C. Guo et al. 10.1109/ACCESS.2019.2950924
16. Calculating Depth for Dark Images Using Self-Supervised Learning: An Investigation of the Role of Edge Maps as Input S. Dubey et al. 10.1109/ACCESS.2025.3556610
17. 3D Vision System for a Robotic Arm Based on Equal Baseline Camera Array A. Kaczmarek 10.1007/s10846-019-01117-8
18. Street-side vehicle detection, classification and change detection using mobile laser scanning data W. Xiao et al. 10.1016/j.isprsjprs.2016.02.007
19. Depth estimation for advancing intelligent transport systems based on self‐improving pyramid stereo network Y. Tian et al. 10.1049/iet-its.2019.0462
20. Auto-LIA: The Automated Vision-Based Leaf Inclination Angle Measurement System Improves Monitoring of Plant Physiology S. Jiang et al. 10.34133/plantphenomics.0245
21. Enhancing Distributed Source Coding With Encoder-Centric Frequency Adaptation and Spatial Transformation H. Xu et al. 10.1109/TMM.2024.3521700
22. ADfM-Net: An Adversarial Depth-From-Motion Network Based on Cross Attention and Motion Enhanced Y. Long et al. 10.1109/LRA.2023.3268885
23. 双目立体视觉研究进展与应用 杨. Yang Xiaoli et al. 10.3788/LOP230457
24. Learning graph-based representations for scene flow estimation M. Zhai et al. 10.1007/s11042-023-15541-4
25. GPDF-Net: geometric prior-guided stereo matching with disparity fusion refinement Q. Zhao et al. 10.1007/s00371-024-03459-3
26. Deep scene flow learning from point cloud with Transformer X. Xiang et al. 10.1016/j.neucom.2025.130350
27. Active Scene Flow Estimation for Autonomous Driving via Real-Time Scene Prediction and Optimal Decision S. Wang et al. 10.1109/TITS.2023.3332399
28. APCAFlow: All-Pairs Cost Volume Aggregation for Optical Flow Estimation M. Feng et al. 10.1109/TMM.2024.3385669
29. A binocular reconstruction based on perspective projection constraints and its application on robot eye‐hand coordination H. Wei & L. Meng 10.1049/cvi2.12091
30. A robust framework for multi-view stereopsis W. Mao et al. 10.1007/s00371-021-02087-5
31. Scene flow estimation from 3D point clouds based on dual‐branch implicit neural representations M. Zhai et al. 10.1049/cvi2.12237
32. Deep Learning in Physical Layer: Review on Data Driven End-to-End Communication Systems and Their Enabling Semantic Applications N. Islam & S. Shin 10.1109/OJCOMS.2024.3425314
33. Extended Reality With HMD-Assisted Guidance and Console 3D Overlay for Robotic Surgery Remote Mentoring C. Li et al. 10.1109/LRA.2024.3455936
34. StereoPairFree: Self-Constructed Stereo Correspondence Network From Natural Images V. Dinh & T. Choi 10.1109/MIS.2022.3193697
35. Detection of Cyclist’s Crossing Intention Based on Posture Estimation for Autonomous Driving A. Abadi et al. 10.1109/JSEN.2023.3234153
36. Unsupervised learning of optical flow in a multi-frame dynamic environment using temporal dynamic modeling Z. Sun et al. 10.1007/s40747-023-01266-2
37. FlowFormer: 3D scene flow estimation for point clouds with transformers Y. Shen & L. Hui 10.1016/j.knosys.2023.111041
38. Object Scene Flow M. Menze et al. 10.1016/j.isprsjprs.2017.09.013
39. Estimation of Motion and Respiratory Characteristics during the Meditation Practice Based on Video Analysis A. Kashevnik et al. 10.3390/s21113771
40. Global Context Volume Construction and Semantics-guided Disparity Refinement for Stereo Matching F. Xu et al. 10.1016/j.neucom.2024.128995
41. Motion Vector Extrapolation for Video Object Detection J. True & N. Khan 10.3390/jimaging9070132
42. Stereo Superpixel Segmentation via Decoupled Dynamic Spatial-Embedding Fusion Network H. Li et al. 10.1109/TMM.2023.3265843
43. Multiscale Neighborhood Cluster Scene Flow Prior for LiDAR Point Clouds J. Gan et al. 10.1109/TGRS.2024.3520209
44. Self-supervised recurrent depth estimation with attention mechanisms I. Makarov et al. 10.7717/peerj-cs.865
45. EBStereo: edge-based loss function for real-time stereo matching W. Bi et al. 10.1007/s00371-023-03002-w
46. Improvement of AnyNet-based end-to-end phased binocular stereo matching network S. Chen et al. 10.1016/j.procs.2022.01.184
47. Estimation and Propagation: Scene Flow Prediction on Occluded Point Clouds K. Wang & S. Shen 10.1109/LRA.2022.3215019
48. Vehicle Localization Using 3D Building Models and Point Cloud Matching A. Ballardini et al. 10.3390/s21165356
49. Deep Shape and SVBRDF Estimation using Smartphone Multi‐lens Imaging C. Fan et al. 10.1111/cgf.14972
50. 基于改进ACV模型的视差估计方法 秦. Qin Lunming et al. 10.3788/LOP240835
51. Parameter selection framework for stereo correspondence P. Nguyen & C. Ahn 10.1007/s00138-020-01076-3
52. Automatic Pseudo-LiDAR Annotation: Generation of Training Data for 3D Object Detection Networks C. Oh et al. 10.1109/ACCESS.2024.3355137
53. OrangeStereo: A navel orange stereo matching network for 3D surface reconstruction Y. Gao et al. 10.1016/j.compag.2024.108626
54. Deep Learning for Scene Flow Estimation on Point Clouds: A Survey and Prospective Trends Z. Li et al. 10.1111/cgf.14795
55. Hierarchical Attention Learning of Scene Flow in 3D Point Clouds G. Wang et al. 10.1109/TIP.2021.3079796
56. Improving IMU-Based Prediction of Lower Limb Kinematics in Natural Environments Using Egocentric Optical Flow A. Sharma & E. Rombokas 10.1109/TNSRE.2022.3156884
57. A Stereo Matching Algorithm for High‐Precision Guidance in a Weakly Textured Industrial Robot Environment Dominated by Planar Facets H. Wei & L. Meng 10.1111/cgf.14435
58. Content Adaptive Distributed Joint Source-Channel Coding for Image Transmission With Hyperprior Y. Li et al. 10.1109/TCCN.2024.3438371
59. Matchability and Uncertainty-Aware Iterative Disparity Refinement for Stereo Matching J. Wang et al. 10.3390/app14188457
60. Efficient Stereo Matching With Adaptive Disparity Range Scaling and Feature Calibration S. Huang et al. 10.1109/JSEN.2024.3491173
61. Coatrsnet: Fully Exploiting Convolution and Attention for Stereo Matching by Region Separation J. Cheng et al. 10.1007/s11263-023-01872-0
62. Road Damage Detection Based on Unsupervised Disparity Map Segmentation R. Fan & M. Liu 10.1109/TITS.2019.2947206
63. Point cloud-based scene flow estimation on realistically deformable objects: A benchmark of deep learning-based methods N. Hermes et al. 10.1016/j.jvcir.2023.103893
64. Pothole Detection Based on Disparity Transformation and Road Surface Modeling R. Fan et al. 10.1109/TIP.2019.2933750
65. MRF-Based Disparity Upsampling Using Stereo Confidence Evaluations X. Meng et al. 10.1109/LSP.2017.2787727
66. Building a Stereo and Wide-View Hybrid RGB/FIR Imaging System for Autonomous Vehicle Y. Zhang et al. 10.1109/JSEN.2021.3131342
67. Multi-Dimensional Cooperative Network for Stereo Matching W. Chen et al. 10.1109/LRA.2021.3130984
68. Motion estimation for large displacements and deformations Q. Chen & C. Poullis 10.1038/s41598-022-21987-7
69. Consistent video depth estimation X. Luo et al. 10.1145/3386569.3392377
70. Efficient Online Segmentation for Sparse 3D Laser Scans I. Bogoslavskyi & C. Stachniss 10.1007/s41064-016-0003-y
71. Neural Distributed Source Coding J. Whang et al. 10.1109/JSAIT.2024.3412976
72. Unsupervised Learning of 3D Scene Flow With LiDAR Odometry Assistance G. Wang et al. 10.1109/TITS.2025.3538765
73. Learning Optical Flow, Depth, and Scene Flow Without Real-World Labels V. Guizilini et al. 10.1109/LRA.2022.3145057
74. S2Net: A Multitask Learning Network for Semantic Stereo of Satellite Image Pairs P. Liao et al. 10.1109/TGRS.2023.3335997
75. Multi-View Depth Estimation by Using Adaptive Point Graph to Fuse Single-View Depth Probabilities K. Wang et al. 10.1109/LRA.2024.3405332
76. Efficient and accurate stereo matching via guided deformable aggregation J. Li et al. 10.1117/1.JEI.34.2.023060
77. Self-Supervised 3D Scene Flow Estimation and Motion Prediction Using Local Rigidity Prior R. Li et al. 10.1109/TPAMI.2024.3401029
78. Learning Dense and Continuous Optical Flow From an Event Camera Z. Wan et al. 10.1109/TIP.2022.3220938
79. Simultaneous Stereo Matching and Confidence Estimation Network T. Schmähling et al. 10.3390/jimaging10080198
80. Stereo disparity estimation based on Siamese network Z. Zhou et al. 10.1088/1361-6501/ad8253
81. Adaptively identify and refine ill-posed regions for accurate stereo matching C. Liu et al. 10.1016/j.neunet.2024.106394
82. Domain gap in adapting self-supervised depth estimation methods for stereo-endoscopy L. Sharan et al. 10.1515/cdbme-2020-0004
83. 3DSF-MixNet: Mixer-Based Symmetric Scene Flow Estimation From 3D Point Clouds S. Wang et al. 10.1109/LRA.2023.3335776
84. Recurrent convolutional model based on gated spiking neural P system for stereo matching networks C. Guo et al. 10.1007/s10489-023-05091-5
85. Optical Flow as Spatial-Temporal Attention Learners Y. Lu et al. 10.1109/TPAMI.2024.3463648
86. Split-Attention Multiframe Alignment Network for Image Restoration Y. Yu et al. 10.1109/ACCESS.2020.2967028
87. Group‐Based Atrous Convolution Stereo Matching Network Q. Zou et al. 10.1155/2021/7386280
88. Unsupervised Learning for Stereo Matching Using Single-View Videos P. Hong & C. Ahn 10.1109/ACCESS.2020.2987875
89. Real-Time Highly Accurate Dense Depth on a Power Budget Using an FPGA-CPU Hybrid SoC O. Rahnama et al. 10.1109/TCSII.2019.2909169
90. Adaptable 2D to 3D Stereo Vision Image Conversion Based on a Deep Convolutional Neural Network and Fast Inpaint Algorithm T. Hachaj 10.3390/e25081212
91. Rethinking Road Surface 3-D Reconstruction and Pothole Detection: From Perspective Transformation to Disparity Map Segmentation R. Fan et al. 10.1109/TCYB.2021.3060461
92. A unified and efficient semi-supervised learning framework for stereo matching F. Xu et al. 10.1016/j.patcog.2023.110128
93. DiffuVolume: Diffusion Model for Volume based Stereo Matching D. Zheng et al. 10.1007/s11263-025-02362-1
94. Supervised biadjacency networks for stereo matching H. Sun et al. 10.1007/s11042-023-15362-5
95. Improved Discrete Optical Flow Estimation With Triple Image Matching Cost F. Yang et al. 10.1109/ACCESS.2020.2968180
96. Deep Learning-Based Incorporation of Planar Constraints for Robust Stereo Depth Estimation in Autonomous Vehicle Applications W. Chuah et al. 10.1109/TITS.2021.3060001