Reference list of currently published stereo methods

DateMethodRes.Reference
06/22/17LocalExpHT. Taniai, Y. Matsushita, Y. Sato, and T. Naemura. Continuous stereo matching using local expansion moves. Submitted to TPAMI 2017.
06/14/17DoGGuidedQM. Kitagawa, I. Shimizu, and R. Sara. High accuracy local stereo matching using DoG scale map. IAPR MVA 2017.
05/23/17r200highHL. Keselman, J. Woodfill, A. Grunnet-Jepsen, and A. Bhowmik. Intel RealSense stereoscopic depth cameras. CCD 2017.
04/04/17DDLQJ. Yin, H. Zhu, D. Yuan, and T. Xue. Sparse representation over discriminative dictionary for stereo matching. Submitted to Pattern Recognition 2017.
03/23/17DSGCAQAnonymous. Deep self-guided cost aggregation for stereo matching. ICCV 2017 submission 1999.
03/22/17JMRHP. Knöbelreiter, C. Reinbacher, A. Shekhovtsov and T. Pock. End-to-end training of hybrid CNN-CRF models for stereo. CVPR 2017.
03/10/17MC-CNN+TDSRFS. Drouyer, S. Beucher, M. Bilodeau, M. Moreaud, and L. Sorbier. Sparse stereo disparity map densifi cation using hierarchical image segmentation. 13th International Symposium on Mathematical Morphology.
03/09/17SGMEPiFAnonymous. Semi-global stereo matching with surface orientation priors. 3DV 2017 submission 56.
01/24/173DMSTHL. Li, X. Yu, S. Zhang, X. Zhao, and L. Zhang. 3D cost aggregation with multiple minimum spanning trees for stereo matching. Applied Optics 56(12):3411-3420, 2017.
01/15/17IGFQR. Hamzah, H. Ibrahim, and A. Hassan. Stereo matching algorithm based on per pixel difference adjustment, iterative guided filter and graph segmentation. Journal of Visual Communication and Image Representation, 42:145-160, 2017.
01/03/17SLACHAnonymous. Sparse locally adaptive cost aggregation for stereo matching. CVPR 2017 submission 3288.
11/24/16ADSMQN. Ma, Y. Men, C. Men, and X. Li. Accurate dense stereo matching based on image segmentation using an adaptive multi-cost approach. Submitted to Symmetry, 2016.
11/16/16MCSCFAnonymous. Simultaneous learning matching cost and smoothness constraint for stereo matching. CVPR 2017 submission 1368.
11/15/16UCNNHAnonymous. Learning to compute the stereo matching cost without supervision. CVPR 2017 submission 2151.
11/15/16MC-CNN-WSHS. Tulyakov, A. Ivanov, and F. Fleuret. Weakly supervised learning of deep metrics for stereo reconstruction. ICCV 2017.
11/14/16PKLSHAnonymous. Integrating prior knowledge into learning-based stereo matching. ICCV 2017 submission 1479.
11/06/16SPSFAnonymous. High-resolution stereo matching based on sampled photoconsistency computation. BMVC 2017 submission 101.
10/23/16SIGMRFQM. Joshi. A learned IGMRF sparseness and IGMRF based regularization framework for dense disparity estimation. Submitted to IPSJ CVA 2016.
10/19/16LW-CNNHH. Park and K. Lee. Look wider to match image patches with convolutional neural network. Submitted to IEEE Signal Processing Letters, 2016.
09/20/16LFSIRQAnonymous. A learned sparseness and IGMRF based regularization framework for dense disparity estimation using unsupervised feature learning. Submitted to IPSJ Transactions on Computer Vision and Applications, 2016.
09/13/16SNP-RSMHS. Zhang, W. Xie, G. Zhang, H. Bao, and M. Kaess. Robust stereo matching with surface normal prediction. ICRA 2017.
08/31/16SEDFAnonymous. Disparity estimation by simultaneous edge drawing. ACCV 2016 Workshop 1 - 3D modelling and applications - Submission id 18.
07/03/16LPUHAnonymous. 3D labeling stereo matching with content aware adaptive windows. 3DV 2016 submission 25.
05/28/16APAP-StereoHM.-G. Park and K.-J. Yoon. As-planar-as-possible depth map estimation. Submitted to IEEE TPAMI 2016.
05/12/16PMSCHL. Li, S. Zhang, X. Yu, and L. Zhang. PMSC: PatchMatch-based superpixel cut for accurate stereo matching. Submitted to IEEE Transactions on Circuits and Systems for Video Technology, 2016.
04/27/16JEMQAnonymous. Stereo matching by joint energy minimization. ECCV 2016 submission 41.
04/24/16HLSC_corHS. Hadfield, K. Lebeda, and R. Bowden. Stereo reconstruction using top-down cues. Submitted to CVIU 2016.
04/13/16GlstereoHZ. Ge. A global stereo matching algorithm with iterative optimization. China CAD & CG 2016 submission 595.
04/12/16MeshStereoExtHC. Zhang, Z. Li, Y. Cheng, R. Cai, H. Chao, and Y. Rui. MeshStereo: a global stereo model with mesh alignment regularization for view interpolation. Submitted to IJCV 2016.
04/03/16ICSGFShahbazi et al. Revisiting intrinsic curves for efficient dense stereo matching. ISPRS Congress 2016 submission 913.
03/15/16MPSVQAnonymous. Morphological processing of stereoscopic image superimpositions for disparity map estimation. ECCV 2016 submission 1308.
02/18/16LS-ELASFR. Ait-Jellal, M. Lange, B. Wassermann, A. Schilling, and A. Zell. LS-ELAS: line segment based efficient large scale stereo matching. ICRA 2017.
01/26/16MC-CNN-fstHJ. Žbontar and Y. LeCun. Stereo matching by training a convolutional neural network to compare image patches. Submitted to JMLR 2015. Code available.
01/21/16MCCNN_LayoutHAnonymous. Stereo depth map refinement with scene layout estimation. CVPR 2016 submission 617.
01/19/16NTDEHK.-R. Kim and C.-S. Kim. Adaptive smoothness constraints for efficient stereo matching using texture and edge information. ICIP 2016.
12/18/15INTSHAnonymous. Image-guided non-local dense matching with three-steps optimization. ISPRS Congress 2016 submission 231.
11/06/15SOU4P-netHAnonymous. Look wider and deeper to match. CVPR 2016 submission 975.
11/05/15GCSVRHAnonymous. High accuracy stereo matching with spatially varying regularization. CVPR 2016 submission 863.
11/03/15MC-CNN+RBSHJ. Barron and B. Poole. The fast bilateral solver. ECCV 2016.
10/13/15MDPHA. Li, D. Chen, Y. Liu, and Z. Yuan. Coordinating multiple disparity proposals for stereo computation. CVPR 2016.
09/28/15R-NCCFS. Fang and Y. Li. Removed based multi-view stereo using window-based matching method. Submitted to MV&A, 2015.
09/14/15ELASFA. Geiger, M. Roser, and R. Urtasun. Efficient large-scale stereo matching. ACCV 2010.
09/14/15ELASHA. Geiger, M. Roser, and R. Urtasun. Efficient large-scale stereo matching. ACCV 2010.
08/28/15MC-CNN-acrtHJ. Žbontar and Y. LeCun. Stereo matching by training a convolutional neural network to compare image patches. Submitted to JMLR 2015. A previous version appeared in CVPR 2015. Code available.
04/19/15MeshStereoHC. Zhang, Z. Li, Y. Cheng, R. Cai, H. Chao, and Y. Rui. MeshStereo: A global stereo model with mesh alignment regularization for view interpolation. ICCV 2015.
04/17/15TMAPHE. Psota, J. Kowalczuk, M. Mittek, and L. Perez. MAP disparity estimation using hidden Markov trees. ICCV 2015.
04/09/15PFSFC. Cigla and A. Alatan. Information permeability for stereo matching. Signal Processing: Image Communication 28(9), 2013.
04/08/15REAFHC. Cigla. Recursive edge-aware filters for stereo matching. CVPR Embedded Vision Workshop 2015.
01/21/15TSGOFM. Mozerov and J. Van de Weijer. Accurate stereo matching by two-step energy minimization. IEEE TIP 24(3):1153-1163, 2015.
11/12/14LCUQAnonymous. Using local cues to improve dense stereo matching. CVPR 2015 submission 973.
10/07/14IDRHJ. Kowalczuk, E. Psota, and L. Perez. Real-time stereo Matching on CUDA using an iterative refinement method for adaptive support-weight correspondences. IEEE TCSVT 23(1):94-104, 2013.
09/18/14SNCCHN. Einecke and J. Eggert. A two-stage correlation method for stereoscopic depth estimation. DICTA 2010.
09/10/14LAMC_DSMHC. Stentoumis, L. Grammatikopoulos, I. Kalisperakis, G. Karras On accurate dense stereo-matching using a local adaptive multi-cost approach. ISPRS Journal of Photogrammetry and Remote Sensing 91:29-49, 2014.
08/31/14BSMQK. Zhang, J. Li, Y. Li, W. Hu, L. Sun, and S. Yang. Binary stereo matching. ICPR 2012.
08/27/14LPSFS. Sinha, D. Scharstein, and R. Szeliski. Efficient high-resolution stereo matching using local plane sweeps. CVPR 2014.
08/25/14LPSHS. Sinha, D. Scharstein, and R. Szeliski. Efficient high-resolution stereo matching using local plane sweeps. CVPR 2014.
07/28/14SGMFH. Hirschmüller. Stereo processing by semi-global matching and mutual information. CVPR 2006; PAMI 30(2):328-341, 2008.
07/28/14SGMHH. Hirschmüller. Stereo processing by semi-global matching and mutual information. CVPR 2006; PAMI 30(2):328-341, 2008.
07/28/14SGBM1HOpenCV 2.4.8 StereoSGBM method, single-pass variant. Reimplementation and modification of H. Hirschmüller's SGM method (CVPR 2006; PAMI 2008).
07/28/14Cens5HH. Hirschmüller, P. Innocent, and J. Garibaldi. Real-time correlation-based stereo vision with reduced border errors. IJCV 47(1-3):229-246, 2002.
07/25/14SGBM1FOpenCV 2.4.8 StereoSGBM method, single-pass variant. Reimplementation and modification of H. Hirschmüller's SGM method (CVPR 2006; PAMI 2008).
07/25/14SGMQH. Hirschmüller. Stereo processing by semi-global matching and mutual information. CVPR 2006; PAMI 30(2):328-341, 2008.
07/25/14SGBM1QOpenCV 2.4.8 StereoSGBM method, single-pass variant. Reimplementation and modification of H. Hirschmüller's SGM method (CVPR 2006; PAMI 2008).
07/25/14SGBM2QOpenCV 2.4.8 StereoSGBM method, full variant (2 passes). Reimplementation of H. Hirschmüller's SGM method (CVPR 2006; PAMI 2008).