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awesome-cbir-papers
📝Awesome and classical image retrieval papers
https://github.com/willard-yuan/awesome-cbir-papers
Last synced: about 3 hours ago
JSON representation
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Classical Local Feature
- Visual Categorization with Bags of Keypoints
- ORB: an efficient alternative to SIFT or SURF
- Three things everyone should know to improve object retrieval
- On-the-fly learning for visual search of large-scale image and video datasets
- All about VLAD
- Aggregating localdescriptors into a compact image representation
- More About VLAD: A Leap from Euclidean to Riemannian Manifolds
- Hamming embedding and weak geometric consistency for large scale image search
- Revisiting the VLAD image representation
- Improving the Fisher Kernel for Large-Scale Image Classification
- Image Classification with the Fisher Vector: Theory and Practice
- A Vote-and-Verify Strategy for Fast Spatial Verification in Image Retrieval
- Triangulation embedding and democratic aggregation for image search
- Efficient Large-scale Image Search With a Vocabulary Tree
- Object retrieval with large vocabularies and fast spatial matching
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Deep Learning Feature (Global Feature)
- Smooth-AP: Smoothing the Path Towards Large-Scale Image Retrieval
- SOLAR: Second-Order Loss and Attention for Image Retrieval
- Unifying Deep Local and Global Features for Image Search
- SOLAR: Second-Order Loss and Attention for Image Retrieval
- A Benchmark on Tricks for Large-scale Image Retrieval
- Learning with Average Precision: Training Image Retrieval with a Listwise Loss
- MultiGrain: a unified image embedding for classes and instances
- End-to-end Learning of Deep Visual Representations for Image retrieval
- What Is the Best Practice for CNNs Applied to Visual Instance Retrieval?
- Cross-dimensional Weighting for Aggregated Deep Convolutional Features
- Aggregating Deep Convolutional Features for Image Retrieval
- Particular object retrieval with integral max-pooling of CNN activations
- Learning to Match Aerial Images with Deep Attentive Architectures
- Siamese Network of Deep Fisher-Vector Descriptors for Image Retrieval
- Combining Fisher Vector and Convolutional Neural Networks for Image Retrieval
- Selective Deep Convolutional Features for Image Retrieval
- Fine-tuning CNN Image Retrieval with No Human Annotation
- An accurate retrieval through R-MAC+ descriptors for landmark recognition
- Regional Attention Based Deep Feature for Image Retrieval - RegionalAttention), BMVC 2018.
- Detect-to-Retrieve: Efficient Regional Aggregation for Image Search
- Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking
- Smooth-AP: Smoothing the Path Towards Large-Scale Image Retrieval
- Learning with Average Precision: Training Image Retrieval with a Listwise Loss
- Bags of Local Convolutional Features for Scalable Instance Search
- SOLAR: Second-Order Loss and Attention for Image Retrieval
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Deep Learning Feature (Local Feature)
- LightGlue: Local Feature Matching at Light Speed
- Simple Learned Keypoints - supervised deep learning keypoint model, arxiv 2023, [code](https://github.com/facebookresearch/silk).
- Learning Super-Features for Image Retrieval
- LoFTR: Detector-Free Local Feature Matching with Transformers
- DFM: A Performance Baseline for Deep Feature Matching
- Learning and aggregating deep local descriptors for instance-level recognition
- DISK: Learning local features with policy gradient - epfl/disk).
- Learning and aggregating deep local descriptorsfor instance-level recognition
- D2D: Keypoint Extraction with Describe to Detect Approach
- UR2KiD: Unifying Retrieval, Keypoint Detection, and Keypoint Description without Local Correspondence Supervision
- Visualizing Deep Similarity Networks
- Beyond Cartesian Representations for Local Descriptors - epfl/log-polar-descriptors), ICCV 2019.
- R2D2: Reliable and Repeatable Detector and Descriptor
- Local Features and Visual Words Emerge in Activations
- Explicit Spatial Encoding for Deep Local Descriptors
- Learning Discriminative Affine Regions via Discriminability - aiki/affnet).
- A Large Dataset for Improving Patch Matching - Dataset](https://github.com/rmitra/PS-Dataset).
- LF-Net: Learning Local Features from Images
- Local Descriptors Optimized for Average Precision
- SuperPoint: Self-Supervised Interest Point Detection and Description
- GeoDesc: Learning Local Descriptors by Integrating Geometry Constraints
- DISK: Learning local features with policy gradient - epfl/disk).
- LightGlue: Local Feature Matching at Light Speed
- Online Invariance Selection for Local Feature Descriptors
- D2D: Keypoint Extraction with Describe to Detect Approach
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Deep Learning Feature (Instance Search)
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ANN search
- Results of the NeurIPS’21 Challenge on Billion-Scale Approximate Nearest Neighbor Search
- Nearest neighbor search with compact codes: A decoder perspective
- Accelerating Large-Scale Inference with Anisotropic Vector Quantization - scann-efficient-vector.html), [code](https://github.com/google-research/google-research/tree/master/scann), ICML 2020.
- Improving Approximate Nearest Neighbor Search through Learned Adaptive Early Termination
- RobustiQ A Robust ANN Search Method for Billion-scale Similarity Search on GPUs
- Zoom: Multi-View Vector Search for Optimizing Accuracy, Latency and Memory
- Vector and Line Quantization for Billion-scale Similarity Search on GPUs
- Learning to Route in Similarity Graphs
- Polysemous codes
- Optimized Product Quantization
- Fast Approximate Nearest Neighbor Search With Navigating Spreading-out Graphs
- Efficient Nearest Neighbors Search for Large-Scale Landmark Recognition
- NV-tree: A Scalable Disk-Based High-Dimensional Index
- Dynamicity and Durability in Scalable Visual Instance Search
- Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors - hnsw).
- Link and code: Fast indexing with graphs and compact regression codes
- A Survey of Product Quantization
- GeoDesc: Learning Local Descriptors by Integrating Geometry Constraints
- Learning a Complete Image Indexing Pipeline
- spreading vectors for similarity search
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CBIR Attack
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CBIR rank
- Fast Spectral Ranking for Similarity Search - aiki/manifold-diffusion), CVPR 2018.
- Fast Spectral Ranking for Similarity Search - aiki/manifold-diffusion), CVPR 2018.
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CBIR in Industry
- Videntifier - scale local feature database, [demo](http://flickrdemo.videntifier.com/), based on SIFT feature and NV-tree. ([Chinese blog post](https://yongyuan.name/blog/videntifier-and-nv-tree.html)).
- Web-Scale Responsive Visual Search at Bing
- Visual Search at Pinterest
- Visual Discovery at Pinterest
- Learning a Unified Embedding for Visual Search at Pinterest
- Deep Learning based Large Scale Visual Recommendation and Search for E-Commerce - incubator/fk-visual-search).
- 微信「扫一扫识物」 的背后技术揭秘
- 揭秘微信「扫一扫」识物为什么这么快？
- Visual Search at Alibaba
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CBIR Competition and Challenge
- The 2021 Image Similarity Dataset and Challenge
- Google Landmark Retrieval Challenge
- Alibaba Large-scale Image Search Challenge
- Pkbigdata image retrieval
- Large-scale Landmark Retrieval/Recognition under a Noisy and Diverse Dataset - 1st-and-3rd-Place-Solution](https://github.com/lyakaap/Landmark2019-1st-and-3rd-Place-Solution).
- The 2021 Image Similarity Dataset and Challenge
- Large-scale Landmark Retrieval/Recognition under a Noisy and Diverse Dataset - 1st-and-3rd-Place-Solution](https://github.com/lyakaap/Landmark2019-1st-and-3rd-Place-Solution).
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CBIR for Duplicate(copy) detection
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Instance Matching
- Neural- Guided RANSAC: Learning Where to Sample Model Hypotheses
- AdaLAM: Revisiting Handcrafted Outlier Detection
- Graph-Cut RANSAC - cut-ransac)
- Image Matching Benchmark
- Robust feature matching in 2.3µs
- openMVG robust_estimation
- Neural-Guided RANSAC: Learning Where to Sample Model Hypotheses
- Homography from two orientation- and scale-covariant features - from-sift-features).
- Homography from two orientation- and scale-covariant features - from-sift-features).
- Neural-Guided RANSAC: Learning Where to Sample Model Hypotheses
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Template Matching
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Image Identification
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Tutorials
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- Compact Features for Visual Search
- Image Similarity using Deep Ranking - similarity-deep-ranking).
- Triplet Loss and Online Triplet Mining in TensorFlow
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- How to Apply Distance Metric Learning to Street-to-Shop Problem
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Slide
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Demo and Demo Online
- Visual Image Retrieval and Localization
- yisou - based painting cbir system, the search algorithm is designed by [Yong Yuan](http://yongyuan.name/).
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Datasets
- Holidays
- Oxford
- Paris
- ROxford and RParis
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
- Holidays
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Useful Package
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Star History
- ![Star History Chart - history.com/#willard-yuan/awesome-cbir-papers&Date)
Categories
Datasets
36
Tutorials
28
Deep Learning Feature (Local Feature)
25
Deep Learning Feature (Global Feature)
25
ANN search
20
Classical Local Feature
15
Instance Matching
10
CBIR in Industry
9
CBIR Competition and Challenge
7
Deep Learning Feature (Instance Search)
4
CBIR rank
2
CBIR for Duplicate(copy) detection
2
Demo and Demo Online
2
Image Identification
1
CBIR Attack
1
Slide
1
Star History
1
Useful Package
1
Template Matching
1
Sub Categories