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Paper list for stereo matching and continue to update this list.

2024

  • MC-Stereo: Multi-peak Lookup and Cascade Search Range for Stereo Matching, M. Feng, J. Cheng, H. Jia, L. Liu, G. Xu, and X. Yang, et al. [Paper][code]. 3DV2024
  • Learning Representations from Foundation Models for Domain Generalized Stereo Matching, Zhang Y, Wang L, Li K, et al. [Paper]. ECCV 2024
  • Temporally Consistent Stereo Matching, Jiaxi Zeng, Chengtang Jiaxi Zeng, Chengtang Ya, et al. [Paper][code]. ECCV 2024
  • Robust Synthetic-to-Real Transfer for Stereo Matching, J. Zhang, J. Li, L. Huang, X. Yu, L. Gu, J. Zheng, and X. Bai, et al. [Paper][code]. CVPR2024
  • LoS: Local Structure Guided Stereo Matching, K. Li, L. Wang, Y. Zhang, K. Xue, S. Zhou and Y. Guo, et al. [Paper][code]. CVPR2024
  • Selective-Stereo: Adaptive Frequency Information Selection for Stereo Matching, Xianqi Wang, Gangwei Xu, et al. [Paper][code]. CVPR2024
  • MoCha-Stereo: Motif Channel Attention Network for Stereo Matching, Ziyang Chen, Wei Long, et al. [Paper][code]. CVPR2024
  • Adaptive Multi-Modal Cross-Entropy Loss for Stereo Matching, Peng Xu, Zhiyu Xiang, et al. [Paper][code]. CVPR2024
  • Neural Markov Random Field for Stereo Matching, Guan, Tongfan, Chen Wang, and Yun-Hui Liu. [Paper][code]. CVPR2024
  • IINet: Implicit Intra-inter Information Fusion for Real-Time Stereo Matching, Ximeng Li, Chen Zhang. [paper[Code]. AAAI2024
  • Any-Stereo: Arbitrary Scale Disparity Estimation for Iterative Stereo Matching, Zhaohuai Liang, Changhe Li. [paper[Code]. AAAI2024
  • TinyStereo: A Tiny Coarse-to-Fine Framework for Vision-Based Depth Estimation on Embedded GPUs,Q. Chang, X. Xu, A. Zha, M. Er, Y. Sun and Y. Li. [Paper]. IEEE Transactions on Systems, Man, and Cybernetics: Systems2024
  • Exploring the Usage of Pre-trained Features for Stereo Matching, J. Zhang, L. Huang, X. Bai, J. Zheng, L. Gu, and E. Hancock, et al. [Paper]. IJCV2024

2023

  • Efficient Spatial-Temporal Stereo Matching Network, Youmin Zhang, Matteo Poggi, et al. [paper][code]. IROS2023
  • DynamicStereo: Consistent Dynamic Depth from Stereo Videos, Nikita Karaev, Ignacio Rocco, et al. [paper][code]. CVPR2023
  • Masked representationlearning for domain generalized stereo matching, Zhibo Rao, Bangshu Xiong, et al. [paper][code]. CVPR2023
  • Domain generalized stereo matchingvia hierarchical visual transformatio, Tianyu Chang, Xun Yang, et al. [paper][code]. CVPR2023
  • Joint Depth Estimation from Gated and Wide-Baseline Active Stereo Cues, Stefanie Walz, Mario Bijelic, et al. [paper][code]. CVPR2023
  • Hybrid Transformer and CNN Attention Network for Stereo Image Super-resolution, Ming Cheng, Haoyu Ma, et al. [paper][code]. CVPR2023
  • Learning to Render Novel Views from Wide-Baseline Stereo Pairs, Yilun Du, Cameron Smit.[paper][code]. CVPR2023
  • Reconstructing Hand in a Point Embedded Multi-view Stereo, Lixin Yang, Jian Xu, et al. [paper][code]. CVPR2023
  • Learning the Distribution of Errors in Stereo Matching for Joint Disparity and Uncertainty Estimation, Liyan Chen, Weihan Wang, et al. [paper][code]. CVPR2023
  • NeRF-Supervised Deep Stereo, Fabio Tosi, Alessio Tonioni, et al. [paper][code]. CVPR2023
  • Implicit View-Time Interpolation of Stereo Videos using Multi-Plane Disparities and Non-Uniform Coordinates, Avinash Paliwal, Andrii Tsarov, et al. [paper]. CVPR2023
  • Enhanced Stable View Synthesis, Nishant Jain, Suryansh Kumar, et al. [paper][code]. CVPR2023
  • Multi-View Azimuth Stereo via Tangent Space Consistency, Xu Cao, Hiroaki Santo, et al. [paper][code]. CVPR2023
  • Category and Joint Agnostic Reconstruction of ARTiculated Objects, Nick Heppert, Muhammad Zubair Irshad, et al. [paper][code]. CVPR2023
  • Scalable, Detailed and Mask-Free Universal Photometric Stereo, Zongrui Li, Qian Zheng, et al. [paper][code]. CVPR2023
  • DANI-Net: Uncalibrated Photometric Stereo by Differentiable Shadow Handling, Anisotropic Reflectance Modeling, and Neural Inverse Rendering, Zongrui Li, Qian Zheng, et al. [paper][code]. CVPR2023
  • On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks, HyunJun Jung, Patrick Ruhkamp, et al. [paper][code]]. CVPR2023
  • Iterative Geometry Encoding Volume for Stereo Matching, Gangwei Xu , Xianqi Wang, et al. [paper][code]. CVPR2023
  • Multi-View Stereo Representation Revisit: Region-Aware MVSNet, Yisu Zhang, Jianke Zhu, et al. [paper][code]. CVPR2023
  • High-frequency Stereo Matching Network, Haoliang Zhao, Huizhou Zhou, et al. [paper][code]. CVPR2023
  • ELFNet: Evidential Local-global Fusion for Stereo Matching, Jieming Lou, Weide Liu, et al. [paper][code]. ICCV2023
  • CroCo v2: Improved Cross-view Completion Pre-training for Stereo Matching and Optical Flow, Weinzaepfel P, Lucas T, Leroy V, et al. [paper][code]. ICCV2023

2022

  • MobileStereoNet: Towards Lightweight Deep Networks for Stereo Matching, Faranak Shamsafar, Samuel Woerz, et al. [paper][code]. WACV2022
  • Towards domain generalized stereo matchingwith a broad-spectrum and task-oriented feature, Biyang Liu, Huimin Yu, et al. [paper][code]. CVPR2022
  • Revisiting Domain Generalized Stereo Matching Networks from a Feature Consistency Perspective, Jiawei Zhang, Xiang Wang, et al. [paper][code]. CVPR2022
  • Practical Stereo Matching via Cascaded Recurrent Network with Adaptive Correlation, Jiankun Li, Peisen Wang, et al. [paper][code]. CVPR2022
  • Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks, Biyang Liu, Huimin Yu, et al. [paper][code]. CVPR2022
  • Attention Concatenation Volume for Accurate and Efficient Stereo Matching, Gangwei Xu, Yun Wang, et al. [paper][code]. CVPR2022
  • An Information-Theoretic Approach to Automatic Shortcut Avoidance and Domain Generalization in Stereo Matching Networks, WeiQin Chuah, Ruwan Tennakoon, et al. [paper][code]. CVPR2022

2021

  • Pyramid Voting Module for End-to-End Self-Supervised Stereo Matching, Hengli Wang, Rui Fan, et al. [paper][code]. ICRA2021
  • Correlate-and-Excite: Real-Time Stereo Matching via Guided Cost Volume Excitation, Antyanta Bangunharcana, Jae Won Cho, et al. [paper][code]. IROS2021
  • A simple andefficient approach for adaptive stereo matching, Xiao Song, Guorun Yang, et al. [paper][code]. CVPR2021
  • A Normalized Disparity Loss for Stereo Matching Networks, Shuya Chen, Zhiyu Xiang, et al. [paper][code]. CVPR2021
  • Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matching, Vladimir Tankovich, Christian Hane, et al. [paper][code]. CVPR2021
  • Stereo Mixture Density Networks, Fabio Tosi, Yiyi Liao, et al. [paper][code]. CVPR2021
  • Cascade and Fused Cost Volume for Robust Stereo Matching, Zhelun Shen, Yuchao Dai, et al. [paper][code]. CVPR2021
  • SMD-Nets: Stereo Mixture Density Networks, Fabio Tosi and Yiyi Liao and Carolin Schmitt and Andreas Geiger. [paper][code]. CVPR2021
  • Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective With Transformers, Zhaoshuo Li, Xingtong Liu, et al. [paper][code]. ICCV2021
  • Multilevel Recurrent Field Transforms for Stereo Matching, Lahav Lipson, Zachary Teed, et al. [paper][code]. 3DV2021

2020

  • Adaptive Unimodal Cost Volume Filtering for Deep Stereo Matching, Youmin Zhang, Yimin Chen, et al. [paper][code]. AAAI2020
  • A Fast and Accurate Network for Disparity Estimation, Qiang Wang, Shaohuai Shi, et al. [Paper][Code]. ICRA2020
  • Domain-invariant stereo matching networks, Feihu Zhang, Xiaojuan Qi, et al. [paper][code]. ECCV2020
  • Cascade and Fused Cost Volume for Robust Stereo Matching, Zhelun Shen, Yuchao Dai, et al. [Paper][Code]. CVPR2020
  • Adaptive Aggregation Network for Efficient Stereo Matching, Haofei Xu, Juyong Zhang, et al. [Paper][Code]. CVPR2020
  • Improving 3D Object Detection With Channel-Wise Transformer, Hualian Sheng, Sijia Cai, et al. [Paper][Code]. CVPR2020
  • Deep Laparoscopic Stereo Matching with Transformers, Xuelian Cheng, Yiran Zhong, et al. [Paper][Code]. NeurIPS2020
  • Matching-space Stereo Networks for Cross-domain Generalization, Changjiang Cai, Matteo Poggi , et al. [paper][code]. 3DV2020

2019

  • Anytime Stereo Image Depth Estimation on Mobile Devices, Yan Wang, Zihang Lai, et al. [Paper][Code]. ICRA2019
  • Learning to adapt for stereo, Alessio Tonioni, Oscar Rahnama, et al. [paper][code]. CVPR2019
  • Real-time self-adaptive deep stereo, Alessio Tonioni, Fabio Tosi, et al. [paper][code]. CVPR2019
  • FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks, Eddy Ilg, Nikolaus Mayer, et al. [Paper][Code]. CVPR2019
  • Group-wise Correlation Stereo Network, Xiaoyang Guo, Kai Yang, et al. [Paper][Code]. CVPR2019
  • Guided Aggregation Net for End-To-End Stereo Matching, Feihu Zhang, Victor Prisacariu, et al. [Paper][Code]. CVPR2019
  • Hierarchical Deep Stereo Matching on High-resolution Images, Gengshan Yang, Joshua Manela, et al. [Paper][Code]. CVPR2019
  • Domain-invariant Stereo Matching Networks, Feihu Zhang, Xiaojuan Qi, et al. [Paper][Code]. CVPR2019
  • Guided Stereo Matching, Matteo Poggi, Davide Pallotti, et al. [Paper][Code]. CVPR2019
  • DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch, Shivam Duggal, Shenlong Wang, et al. [Paper][Code]. ICCV2019
  • AutoDispNet: Improving Disparity Estimation With AutoML, Tonmoy Saikia, Yassine Marrakchi, et al. [Paper][Code]. ICCV2019
  • On the over-smoothing problem of cnn based disparity estimation, Chuangrong Chen, Xiaozhi Chen, et al. [Paper][Code]. ICCV2019

2018

  • Deep Stereo Matching with Explicit Cost Aggregation Sub-Architecture, Lidong Yu, Yucheng Wang, Yuwei Wu, Yunde Jia. [Paper]. AAAI2018
  • Generalizing deep stereo matching to novel domains, Jiahao Pang, Wenxiu Sun, et al. [paper][code]. CVPR2018
  • Pyramid Stereo Matching Network, Jia-Ren Chang,Yong-Sheng Chen, et al. [Paper][Code]. CVPR2018
  • StereoNet: Guided Hierarchical Refinement for Real-Time Edge-Aware Depth Prediction, Sameh Khamis, Sean Fanello, et al. [Paper][Code]. ECCV2018
  • Learning Monocular Depth by Distilling Cross-domain Stereo Networks, Xiaoyang Guo, Hongsheng Li, et al. [paper][code]. ECCV2018

Dataset

  • Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo, Lukas Mehl, Jenny Schmalfuss, et al. [paper][code]. CVPR2023
  • SMD-Nets: Stereo Mixture Density Networks(UnrealStereo4K), Fabio Tosi, Yiyi Liao, et al. [paper][code]. CVPR2021
  • Virtual KITTI 2(Virtual KITTI 2), Yohann Cabon, Naila Murray, et al. [paper][Homepage]. arxiv
  • DrivingStereo: A Large-Scale Dataset for Stereo Matching in Autonomous Driving Scenarios(DrivingStereo), Guorun Yang, Xiao Song. [Paper][Homepage]. CVPR2019
  • A Multi-View Stereo Benchmark with High-Resolution Images and Multi-Camera Videos(ETH3D), Thomas Sch¨ops, Johannes L. [Paper][Homepage]. CVPR2017
  • A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation(SceneFlow), Nikolaus Mayer, Eddy Ilg. [Paper][Download]. CVPR2016
  • Virtual Worlds as Proxy for Multi-Object Tracking Analysis(Virtual KITTI), Adrien Gaidon, Qiao Wang. [Paper][Homepage]. CVPR2016
  • Object Scene Flow for Autonomous Vehicles(KITTI 15), Moritz Menze, Andreas Geiger. [Paper][Homepage]. CVPR2015
  • High-Resolution Stereo Datasets with Subpixel-Accurate Ground Truth(Middlebury), Daniel Scharstein, Heiko Hirschm¨uller. [Paper][Homepage]. GCPR2014
  • Are we ready for Autonomous Driving? The KITTI Vision Benchmark Suite(KITTI 12), Andreas Geiger, Philip Lenz. [Paper][Homepage]. CVPR2012