mlsanityData to 7 Oct 2026

Iterative Geometry Encoding Volume for Stereo Matching

arXiv 2303.06615 ↗First posted 12 Mar 2023cs.CVcited by 188

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Abstract (arXiv)

Recurrent All-Pairs Field Transforms (RAFT) has shown great potentials in matching tasks. However, all-pairs correlations lack non-local geometry knowledge and have difficulties tackling local ambiguities in ill-posed regions. In this paper, we propose Iterative Geometry Encoding Volume (IGEV-Stereo), a new deep network architecture for stereo matching. The proposed IGEV-Stereo builds a combined geometry encoding volume that encodes geometry and context information as well as local matching details, and iteratively indexes it to update the disparity map. To speed up the convergence, we exploit GEV to regress an accurate starting point for ConvGRUs iterations. Our IGEV-Stereo ranks 1st on KITTI 2015 and 2012 (Reflective) among all published methods and is the fastest among the top 10 methods. In addition, IGEV-Stereo has strong cross-dataset generalization as well as high inference efficiency. We also extend our IGEV to multi-view stereo (MVS), i.e. IGEV-MVS, which achieves competitive accuracy on DTU benchmark. Code is available at https://github.com/gangweiX/IGEV.

Key facts. Cited by 188 papers in the map (data through 7 Oct 2026). Builds on 41 of its 60 references that are in the map. First posted on arXiv 12 Mar 2023.

Builds on

41 of 60 references.

References · 41

  1. 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,016
  2. 2022A ConvNet for the 2020scited by 3,545
  3. 2020RAFT: Recurrent All-Pairs Field Transforms for Optical Flowcited by 2,385
  4. 2015A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimationcited by 878
  5. 2018MVSNet: Depth Inference for Unstructured Multi-view Stereocited by 780
  6. 2018Pyramid Stereo Matching Networkcited by 486
  7. 2019Cascade Cost Volume for High-Resolution Multi-View Stereo and Stereo Matchingcited by 414
  8. 2017End-to-End Learning of Geometry and Context for Deep Stereo Regressioncited by 359
  9. 2021RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo Matchingcited by 348
  10. 2019Recurrent MVSNet for High-resolution Multi-view Stereo Depth Inferencecited by 252
  11. 2019GA-Net: Guided Aggregation Net for End-to-end Stereo Matchingcited by 242
  12. 2019Group-wise Correlation Stereo Networkcited by 235
29 more
  1. 2020PatchmatchNet: Learned Multi-View Patchmatch Stereocited by 204
  2. 2022Practical Stereo Matching via Cascaded Recurrent Network with Adaptive Correlationcited by 197
  3. 2020Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective with Transformerscited by 190
  4. 2020Hierarchical Neural Architecture Search for Deep Stereo Matchingcited by 166
  5. 2019Cost Volume Pyramid Based Depth Inference for Multi-View Stereocited by 154
  6. 2021CFNet: Cascade and Fused Cost Volume for Robust Stereo Matchingcited by 153
  7. 2019Deep Stereo using Adaptive Thin Volume Representation with Uncertainty Awarenesscited by 151
  8. 2019Point-Based Multi-View Stereo Networkcited by 147
  9. 2018Learning Depth with Convolutional Spatial Propagation Networkcited by 135
  10. 2022Attention Concatenation Volume for Accurate and Efficient Stereo Matchingcited by 130
  11. 2020HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matchingcited by 120
  12. 2019DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatchcited by 114
  13. 2019Domain-invariant Stereo Matching Networkscited by 108
  14. 2020Fast-MVSNet: Sparse-to-Dense Multi-View Stereo With Learned Propagation and Gauss-Newton Refinementcited by 105
  15. 2018SegStereo: Exploiting Semantic Information for Disparity Estimationcited by 88
  16. 2021AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Networkcited by 71
  17. 2022Accurate and Efficient Stereo Matching via Attention Concatenation Volumecited by 59
  18. 2021IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereocited by 56
  19. 2019Adaptive Unimodal Cost Volume Filtering for Deep Stereo Matchingcited by 55
  20. 2022Multiview Stereo with Cascaded Epipolar RAFTcited by 51
  21. 2021Correlate-and-Excite: Real-Time Stereo Matching via Guided Cost Volume Excitationcited by 47
  22. 2021Bilateral Grid Learning for Stereo Matching Networkscited by 46
  23. 2022Revisiting Domain Generalized Stereo Matching Networks from a Feature Consistency Perspectivecited by 46
  24. 2021MVS2D: Efficient Multi-view Stereo via Attention-Driven 2D Convolutionscited by 43
  25. 2022GraftNet: Towards Domain Generalized Stereo Matching with a Broad-Spectrum and Task-Oriented Featurecited by 43
  26. 2019EdgeStereo: An Effective Multi-Task Learning Network for Stereo Matching and Edge Detectioncited by 39
  27. 2021Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networkscited by 32
  28. 2021PVStereo: Pyramid Voting Module for End-to-End Self-Supervised Stereo Matchingcited by 28
  29. 2021A Decomposition Model for Stereo Matchingcited by 25

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 12; 2024: 67; 2025: 65; 2026: 44.

188 papers.

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  1. 2025Depth Anything 3: Recovering the Visual Space from Any Viewscited by 626
  2. 2024Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimationcited by 389
  3. 2025FoundationStereo: Zero-Shot Stereo Matchingcited by 168
  4. 2024Selective-Stereo: Adaptive Frequency Information Selection for Stereo Matchingcited by 98
  5. 2024Prompting Depth Anything for 4K Resolution Accurate Metric Depth Estimationcited by 73
  6. 2024GS2Mesh: Surface Reconstruction from Gaussian Splatting via Novel Stereo Viewscited by 65
  7. 2025DEFOM-Stereo: Depth Foundation Model Based Stereo Matchingcited by 51
  8. 2024MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View Stereocited by 49
  9. 2024MoCha-Stereo: Motif Channel Attention Network for Stereo Matchingcited by 48
  10. 2025Pixel-Perfect Depth with Semantics-Prompted Diffusion Transformerscited by 47
  11. 2024Stereo Anywhere: Robust Zero-Shot Deep Stereo Matching Even Where Either Stereo or Mono Failcited by 45
  12. 2024TAPTR: Tracking Any Point with Transformers as Detectioncited by 43
38 more
  1. 2024Neural Markov Random Field for Stereo Matchingcited by 38
  2. 2024HDRFlow: Real-Time HDR Video Reconstruction with Large Motionscited by 30
  3. 2024Adaptive Fusion of Single-View and Multi-View Depth for Autonomous Drivingcited by 30
  4. 2023OpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong Baselinecited by 28
  5. 2024LightStereo: Channel Boost Is All You Need for Efficient 2D Cost Aggregationcited by 28
  6. 2024Match-Stereo-Videos: Bidirectional Alignment for Consistent Dynamic Stereo Matchingcited by 24
  7. 2024Playing to Vision Foundation Model's Strengths in Stereo Matchingcited by 23
  8. 2024A Survey on Deep Stereo Matching in the Twentiescited by 23
  9. 2025Fast-FoundationStereo: Real-Time Zero-Shot Stereo Matchingcited by 23
  10. 2024OmniNOCS: A unified NOCS dataset and model for 3D lifting of 2D objectscited by 22
  11. 2023Adaptive Multi-Modal Cross-Entropy Loss for Stereo Matchingcited by 19
  12. 2023Global Occlusion-Aware Transformer for Robust Stereo Matchingcited by 19
  13. 2025MonSter++: Unified Stereo Matching, Multi-view Stereo, and Real-time Stereo with Monodepth Priorscited by 19
  14. 2023Revisiting Depth Completion from a Stereo Matching Perspective for Cross-domain Generalizationcited by 18
  15. 2024Learning-based Multi-View Stereo: A Surveycited by 18
  16. 2025Multi-view Reconstruction via SfM-guided Monocular Depth Estimationcited by 17
  17. 2023DiffuVolume: Diffusion Model for Volume based Stereo Matchingcited by 16
  18. 2024All-in-One: Transferring Vision Foundation Models into Stereo Matchingcited by 16
  19. 2025StereoVLA: Enhancing Vision-Language-Action Models with Stereo Visioncited by 16
  20. 2024Robust Synthetic-to-Real Transfer for Stereo Matchingcited by 15
  21. 2025BridgeDepth: Bridging Monocular and Stereo Reasoning with Latent Alignmentcited by 15
  22. 2024S3M-Net: Joint Learning of Semantic Segmentation and Stereo Matching for Autonomous Drivingcited by 14
  23. 2025Learning Robust Stereo Matching in the Wild with Selective Mixture-of-Expertscited by 13
  24. 2024Federated Online Adaptation for Deep Stereocited by 12
  25. 2024Temporal Event Stereo via Joint Learning with Stereoscopic Flowcited by 12
  26. 2025BANet: Bilateral Aggregation Network for Mobile Stereo Matchingcited by 12
  27. 2024Learning Intra-view and Cross-view Geometric Knowledge for Stereo Matchingcited by 11
  28. 2024Match Stereo Videos via Bidirectional Alignmentcited by 11
  29. 2025Diving into the Fusion of Monocular Priors for Generalized Stereo Matchingcited by 10
  30. 2023ADFactory: An Effective Framework for Generalizing Optical Flow with Nerfcited by 9
  31. 2023Memory-Efficient Optical Flow via Radius-Distribution Orthogonal Cost Volumecited by 9
  32. 2023RSRD: A Road Surface Reconstruction Dataset and Benchmark for Safe and Comfortable Autonomous Drivingcited by 8
  33. 2024RoadBEV: Road Surface Reconstruction in Bird's Eye Viewcited by 8
  34. 2025Self-Supervised Sparse Sensor Fusion for Long Range Perceptioncited by 8
  35. 2025StereoAdapter: Adapting Stereo Depth Estimation to Underwater Scenescited by 8
  36. 2024ClearDepth: Enhanced Stereo Perception of Transparent Objects for Robotic Manipulationcited by 7
  37. 2024SpatialMe: Stereo Video Conversion Using Depth-Warping and Blend-Inpaintingcited by 7
  38. 2025Stereo Any Video: Temporally Consistent Stereo Matchingcited by 7

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