mlsanityData to 7 Oct 2026

Correspondence Networks with Adaptive Neighbourhood Consensus

arXiv 2003.12059 ↗First posted 26 Mar 2020cs.CVcited by 42

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Abstract (arXiv)

In this paper, we tackle the task of establishing dense visual correspondences between images containing objects of the same category. This is a challenging task due to large intra-class variations and a lack of dense pixel level annotations. We propose a convolutional neural network architecture, called adaptive neighbourhood consensus network (ANC-Net), that can be trained end-to-end with sparse key-point annotations, to handle this challenge. At the core of ANC-Net is our proposed non-isotropic 4D convolution kernel, which forms the building block for the adaptive neighbourhood consensus module for robust matching. We also introduce a simple and efficient multi-scale self-similarity module in ANC-Net to make the learned feature robust to intra-class variations. Furthermore, we propose a novel orthogonal loss that can enforce the one-to-one matching constraint. We thoroughly evaluate the effectiveness of our method on various benchmarks, where it substantially outperforms state-of-the-art methods.

Key facts. Cited by 42 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Mar 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 11; 2022: 14; 2023: 6; 2024: 5; 2025: 2; 2026: 4.

42 papers.

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  1. 2021Hypercorrelation Squeeze for Few-Shot Segmentationcited by 193
  2. 2022AiATrack: Attention in Attention for Transformer Visual Trackingcited by 137
  3. 2022Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot Segmentationcited by 114
  4. 2021CATs: Cost Aggregation Transformers for Visual Correspondencecited by 77
  5. 2021Relational Embedding for Few-Shot Classificationcited by 74
  6. 2022CATs++: Boosting Cost Aggregation with Convolutions and Transformerscited by 53
  7. 2022Correlation Verification for Image Retrievalcited by 47
  8. 2021Convolutional Hough Matching Networkscited by 43
  9. 2023SD4Match: Learning to Prompt Stable Diffusion Model for Semantic Matchingcited by 38
  10. 2022Visual correspondence-based explanations improve AI robustness and human-AI team accuracycited by 37
  11. 2021Multi-scale Matching Networks for Semantic Correspondencecited by 32
  12. 2022Neural Matching Fields: Implicit Representation of Matching Fields for Visual Correspondencecited by 32
30 more
  1. 2022Learning Semantic Correspondence with Sparse Annotationscited by 31
  2. 2021Deep Matching Prior: Test-Time Optimization for Dense Correspondencecited by 30
  3. 2022Probabilistic Warp Consistency for Weakly-Supervised Semantic Correspondencescited by 30
  4. 2022TransforMatcher: Match-to-Match Attention for Semantic Correspondencecited by 29
  5. 2023ASIC: Aligning Sparse in-the-wild Image Collectionscited by 26
  6. 2023FECANet: Boosting Few-Shot Semantic Segmentation with Feature-Enhanced Context-Aware Networkcited by 22
  7. 2022MSANet: Multi-Similarity and Attention Guidance for Boosting Few-Shot Segmentationcited by 21
  8. 2021The Animation Transformer: Visual Correspondence via Segment Matchingcited by 20
  9. 2024Distillation of Diffusion Features for Semantic Correspondencecited by 17
  10. 2021Cost Aggregation Is All You Need for Few-Shot Segmentationcited by 16
  11. 2022Semi-Supervised Learning of Semantic Correspondence with Pseudo-Labelscited by 16
  12. 2024Unifying Feature and Cost Aggregation with Transformers for Semantic and Visual Correspondencecited by 14
  13. 2021Convolutional Hough Matching Networks for Robust and Efficient Visual Correspondencecited by 12
  14. 2022Demystifying Unsupervised Semantic Correspondence Estimationcited by 9
  15. 2021DenseGAP: Graph-Structured Dense Correspondence Learning with Anchor Pointscited by 8
  16. 2022Integrative Feature and Cost Aggregation with Transformers for Dense Correspondencecited by 6
  17. 2023SimSC: A Simple Framework for Semantic Correspondence with Temperature Learningcited by 6
  18. 2023Efficient Semantic Matching with Hypercolumn Correlationcited by 6
  19. 2024Beyond Mask: Rethinking Guidance Types in Few-shot Segmentationcited by 3
  20. 2025Semantic Correspondence: Unified Benchmarking and a Strong Baselinecited by 3
  21. 2026MARCO: Navigating the Unseen Space of Semantic Correspondencecited by 3
  22. 2021Understanding Pixel-level 2D Image Semantics with 3D Keypoint Knowledge Enginecited by 2
  23. 2023Match me if you can: Semi-Supervised Semantic Correspondence Learning with Unpaired Imagescited by 2
  24. 2024Independently Keypoint Learning for Small Object Semantic Correspondencecited by 2
  25. 2025Similarity-Aware Selective State-Space Modeling for Semantic Correspondencecited by 1
  26. 2022Joint Learning of Feature Extraction and Cost Aggregation for Semantic Correspondencecited by 0
  27. 2024Boosting Few-Shot Segmentation via Instance-Aware Data Augmentation and Local Consensus Guided Cross Attentioncited by 0
  28. 2026SimpleMatch: A Simple and Strong Baseline for Semantic Correspondencecited by 0
  29. 2026AffordMatcher: Affordance Learning in 3D Scenes from Visual Signifierscited by 0
  30. 2026DreamSat-Pose: Spacecraft Pose Estimation from Single-View 3D Reconstructions and Learned 2D-3D Feature Matchingcited by 0