Awesome image retrieval papers
The main goal is to collect classical and solid works of image retrieval in academia and industry.
- Classical Local Feature
- Deep Learning Feature (Global Feature)
- Deep Learning Feature (Local Feature)
- Deep Learning Feature (Instance Search)
- ANN search
- CBIR Attack
- CBIR rank
- CBIR in Industry
- CBIR Competition and Challenge
- CBIR for Duplicate(copy) detection
- Feature Fusion
- Instance Matching
- Semantic Matching
- Template Matching
- Image Identification
- Tutorials
- Slide
- Demo and Demo Online
- Datasets
- Useful Package
Classical Local Feature
- Object retrieval with large vocabularies and fast spatial matching, CVPR 2007.
- Visual Categorization with Bags of Keypoints, ECCV 2004.
- ORB: an efficient alternative to SIFT or SURF, ICCV 2011.
- Object Recognition from Local Scale-Invariant Features, ICCV 1999.
- Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval, ICCV 2007.
- Three things everyone should know to improve object retrieval, CVPR 2012.
- On-the-fly learning for visual search of large-scale image and video datasets
- All about VLAD, CVPR 2013.
- Aggregating localdescriptors into a compact image representation, CVPR 2010.
- More About VLAD: A Leap from Euclidean to Riemannian Manifolds, CVPR 2015.
- Hamming embedding and weak geometric consistency for large scale image search, CVPR 2008.
- Revisiting the VLAD image representation, project
- Improving the Fisher Kernel for Large-Scale Image Classification, ECCV 2010.
- Image Classification with the Fisher Vector: Theory and Practice
- Democratic Diffusion Aggregation for ImageRetrieval
- A Vote-and-Verify Strategy for Fast Spatial Verification in Image Retrieval, ACCV 2016.
- Triangulation embedding and democratic aggregation for image search, CVPR 2014.
- Efficient Large-scale Image Search With a Vocabulary Tree, IPOL 2015, code.
Deep Learning Feature (Global Feature)
- Online Invariance Selection for Local Feature Descriptors, ECCV 2020, code.
- Smooth-AP: Smoothing the Path Towards Large-Scale Image Retrieval, ECCV 2020.
- SOLAR: Second-Order Loss and Attention for Image Retrieval, ECCV 2020.
- Unifying Deep Local and Global Features for Image Search, arxiv 2020.
- SOLAR: Second-Order Loss and Attention for Image Retrieval, arxiv 2020.
- A Benchmark on Tricks for Large-scale Image Retrieval，arxiv 2020.
- Learning with Average Precision: Training Image Retrieval with a Listwise Loss, ICCV 2019.
- MultiGrain: a unified image embedding for classes and instances, arxiv 2019.
- Deep Image Retrieval:Learning Global Representations for Image search.
- End-to-end Learning of Deep Visual Representations for Image retrieval, DIR更详细的论文说明.
- What Is the Best Practice for CNNs Applied to Visual Instance Retrieval?, 关于layer选取的问题.
- Bags of Local Convolutional Features for Scalable Instance Search.
- Faster R-CNN Features for Instance Search, CVPR workshop 2016.
- Cross-dimensional Weighting for Aggregated Deep Convolutional Features, project.
- Class-Weighted Convolutional Features for Image Retrieval.
- Multi-Scale Orderless Pooling of Deep Convolutional Activation Features, VLAD coding.
- Aggregating Deep Convolutional Features for Image Retrieval, 论文笔记, 基于深度学习的视觉实例搜索研究进展.
- Particular object retrieval with integral max-pooling of CNN activations, project.
- Particular object retrieval using CNN.
- 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, fv和cnn特征融合提升.
- Selective Deep Convolutional Features for Image Retrieval, ACM MM 2017.
- Class-Weighted Convolutional Features for Image Retrieval.
- Fine-tuning CNN Image Retrieval with No Human Annotation, TPAMI 2018.
- An accurate retrieval through R-MAC+ descriptors for landmark recognition.
- Regional Attention Based Deep Feature for Image Retrieval, code, BMVC 2018.
- Detect-to-Retrieve: Efficient Regional Aggregation for Image Search, CVPR 2019.
- Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking, project, CVPR 2018.
- Guided Similarity Separation for Image Retrieval, NeurIPS 2019.
Deep Learning Feature (Local Feature)
- Simple Learned Keypoints, a self-supervised deep learning keypoint model, arxiv 2023, code.
- Learning Super-Features for Image Retrieval, ICLR 2022, code.
- LoFTR: Detector-Free Local Feature Matching with Transformers, CVPR 2021, code.
- DFM: A Performance Baseline for Deep Feature Matching, CVPRW 2021, code.
- COTR: Correspondence Transformer for Matching Across Images, arxiv 2021.
- Online Invariance Selection for Local Feature Descriptors, ECCV 2020, code.
- Learning and aggregating deep local descriptors for instance-level recognition, ECCV 2020, code.
- DISK: Learning local features with policy gradient, NeurIPS 2020, code.
- Learning and aggregating deep local descriptorsfor instance-level recognition, ECCV 2020, code.
- D2D: Keypoint Extraction with Describe to Detect Approach, arxiv 2020.
- UR2KiD: Unifying Retrieval, Keypoint Detection, and Keypoint Description without Local Correspondence Supervision, arxiv.
- Visualizing Deep Similarity Networks, WACV 2019.
- Combination of Multiple Global Descriptors for Image Retrieval.
- Beyond Cartesian Representations for Local Descriptors, code, ICCV 2019.
- R2D2: Reliable and Repeatable Detector and Descriptor, code, NeurIPS 2019.
- SOSNet: Second Order Similarity Regularization for Local Descriptor Learning, CVPR 2019.
- Local Features and Visual Words Emerge in Activations, CVPR 2019.
- Explicit Spatial Encoding for Deep Local Descriptors, CVPR 2019.
- Key.Net: Keypoint Detection by Handcrafted and Learned CNN Filters, ICCV 2019.
- Learning Discriminative Affine Regions via Discriminability, affnet.
- A Large Dataset for Improving Patch Matching, PS-Dataset.
- Working hard to know your neighbor's margins: Local descriptor learning loss, code.
- MatchNet: Unifying Feature and Metric Learning for Patch-Based Matching, code.
- LF-Net: Learning Local Features from Images, NeurIPS 2018.
- Local Descriptors Optimized for Average Precision, CVPR 2018.
- SuperPoint: Self-Supervised Interest Point Detection and Description, Magic Leap.
- GeoDesc: Learning Local Descriptors by Integrating Geometry Constraints, code, ECCV 2018.
- Learning local feature descriptors with triplets and shallow convolutional neural networks, BMVC 2016.
Deep Learning Feature (Instance Search)
- Deeply Activated Salient Region for Instance Search, arXiv 2020.
- Instance search based on weakly supervised feature learning, Neurocomputing 2019.
- Instance Search via Instance Level Segmentation and Feature Representation, arXiv 2018.
- Unsupervised object discovery for instance recognition, WACV 2018.
- Faster R-CNN Features for Instance Search, CVPR workshop 2016.
ANN search
- Results of the NeurIPS’21 Challenge on Billion-Scale Approximate Nearest Neighbor Search.
- Nearest neighbor search with compact codes: A decoder perspective, arxiv 2021.
- Accelerating Large-Scale Inference with Anisotropic Vector Quantization, blog, code, ICML 2020.
- Improving Approximate Nearest Neighbor Search through Learned Adaptive Early Termination, SIGMOD 2020.
- RobustiQ A Robust ANN Search Method for Billion-scale Similarity Search on GPUs, ICMR 2019.
- Zoom: Multi-View Vector Search for Optimizing Accuracy, Latency and Memory.
- Vector and Line Quantization for Billion-scale Similarity Search on GPUs.
- GGNN: Graph-based GPU Nearest Neighbor Search, arxiv 2019, code.
- Learning to Route in Similarity Graphs, ICML 2019.
- Practical and Optimal LSH for Angular Distance.
- pq-fast-scan.
- faiss. A library for efficient similarity search and clustering of dense vectors.
- Polysemous codes.
- Optimized Product Quantization.
- lopq. Training of Locally Optimized Product Quantization (LOPQ) models for approximate nearest neighbor search of high dimensional data in Python and Spark.
- nns_benchmark. Benchmark of Nearest Neighbor Search on High Dimensional Data.
- Optimized Product Quantization.
- Falconn. FAst Lookups of Cosine and Other Nearest Neighbors.
- Annoy. Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk.
- NMSLIB. Non-Metric Space Library (NMSLIB): A similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.
- Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs, graph-based method.
- Fast Approximate Nearest Neighbor Search With Navigating Spreading-out Graphs, code
- 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，code.
- Link and code: Fast indexing with graphs and compact regression codes.
- A Survey of Product Quantization，对于矢量量化方法一篇比较完整的调研，值得一读.
- GeoDesc: Learning Local Descriptors by Integrating Geometry Constraints，学习局部特征的descriptor，匹配能力较强.
- Learning a Complete Image Indexing Pipeline, CVPR 2018.
- spreading vectors for similarity search, ICLR 2019.
- SPTAG: A library for fast approximate nearest neighbor search. Microsoft.
CBIR Attack
CBIR rank
- Fast Spectral Ranking for Similarity Search, code, CVPR 2018.
CBIR in Industry
- Videntifier is a visual search engine based on a patented large-scale local feature database, demo, based on SIFT feature and NV-tree. (Chinese blog post).
- Web-Scale Responsive Visual Search at Bing.
- Visual Search at Alibaba.
- Visual Search at Pinterest.
- Visual Discovery at Pinterest.
- Learning a Unified Embedding for Visual Search at Pinterest, KDD 2019.
- Visual Search at ebay.
- Deep Learning based Large Scale Visual Recommendation and Search for E-Commerce, project.
- 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？
CBIR Competition and Challenge
- The 2021 Image Similarity Dataset and Challenge, 2021, code.
- Google Landmark Retrieval Challenge, 2018.
- Alibaba Large-scale Image Search Challenge, 2015.
- Pkbigdata image retrieval, 2015.
- Large-scale Landmark Retrieval/Recognition under a Noisy and Diverse Dataset, Landmark2019-1st-and-3rd-Place-Solution.
CBIR for Duplicate(copy) detection
- A Self-Supervised Descriptor for Image Copy Detection, CVPR 2022, code.
- A Robust and Fast Video Copy Detection System Using Content-Based Fingerprinting.
Feature Fusion
Instance Matching
- Neural- Guided RANSAC: Learning Where to Sample Model Hypotheses, ICCV 2019, code.
- AdaLAM: Revisiting Handcrafted Outlier Detection, arxiv 2006.
- Graph-Cut RANSAC, code
- Image Matching Benchmark
- GMS: Grid-based Motion Statistics for Fast, Ultra-robust Feature Correspondence
- A Vote-and-Verify Strategy for Fast Spatial Verification in Image Retrieval
- CODE: Coherence Based Decision Boundaries for Feature Correspondence
- Robust feature matching in 2.3µs
- PopSift is an implementation of the SIFT algorithm in CUDA
- openMVG robust_estimation
- Neural-Guided RANSAC: Learning Where to Sample Model Hypotheses.
- Homography from two orientation- and scale-covariant features, code.
Semantic Matching
Template Matching
Image Identification
- Image Identification Using SIFT Algorithm: Performance Analysis against Different Image Deformations.
Tutorials
- PyRetri, Open source deep learning based image retrieval toolbox based on PyTorch.
- How to Apply Distance Metric Learning to Street-to-Shop Problem.
- Recent Image Search Techniques.
- Compact Features for Visual Search.
- multimedia-indexing. A framework for large-scale feature extraction, indexing and retrieval.
- Image Similarity using Deep Ranking, code.
- Triplet Loss and Online Triplet Mining in TensorFlow.
- tf_retrieval_baseline.
Slide
- VRG Prague in “Large-Scale Landmark Recognition Challenge”, ranked 3rd in the Google Landmark Recognition Challenge.
Demo and Demo Online
- Visual Image Retrieval and Localization, SIFT feature encoded by BOW.
- VGG Image Search Engine, SIFT feature encoded by BOW.
- SoTu, A flask-based cbir system.
- yisou, A flask-based painting cbir system, the search algorithm is designed by Yong Yuan.
Datasets
- DeepFashion2 Dataset, DeepFashion2 is a comprehensive fashion dataset.
- Holidays, Holidays consists images from personal holiday albums of various scene types.
- Oxford, Oxford consists of 11 different Oxford landmarks.
- Paris, Paris consists of images crawled from 11 queries on specific Paris architecture.
- ROxford and RParis, ROxford and RParis are revisited versions of the original Oxford and Paris with annotation corrections, enlarged sizes and more difficult samples.
- INSTRE, INSTRE is an instance-level object retrieval dataset.