kmjz/awesome-cbir-papers

📝Awesome and classical image retrieval papers

CBIR in academia and industry

Awesome image retrieval papers

The main goal is collect classical and solid work of image retrieval in academia and industry.

• ARXIV
• Local Feature Based
• Deep Learning Feature (Global Feature)
• Deep Learning Feature (Local Feature)
• ANN search
• CBIR rank
• CBIR in Industry
• CBIR Competition and Challenge
• CBIR for Duplicate(copy) detection
• Feature Fusion
• Instance Matching
• Semantic Matching
• Image Identification
• Tutorials
• Demo and Demo Online
• Datasets
• Useful Package

ARXIV

• A Benchmark on Tricks for Large-scale Image Retrieval，通用图像检索各种trick介绍。
• Learning with Average Precision: Training Image Retrieval with a Listwise Loss, deep image retrieval续作。
• MultiGrain: a unified image embedding for classes and instances，Hervé Jégou, Andrea Vedaldi, Matthijs Douze，三牛首次出现在同一paper中。将相似和实例检索统一在一个框架中。
• Composing Text and Image for Image Retrieval - An Empirical Odyssey
• Visualizing Deep Similarity Networks
• Combination of Multiple Global Descriptors for Image Retrieval

Local Feature Based

• Object retrieval with large vocabularies and fast spatial matching
• Visual Categorization with Bags of Keypoints
• ORB: an efficient alternative to SIFT or SURF
• Object Recognition from Local Scale-Invariant Features
• Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval
• 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 representatio
• 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, project
• Improving the Fisher Kernel for Large-Scale Image Classification
• 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
• Triangulation embedding and democratic aggregation for image search
• Efficient Large-scale Image Search With a Vocabulary Tree, code

Deep Learning Feature (Global Feature)

• SOLAR: Second-Order Loss and Attention for Image Retrieval, arxiv 2020.
• 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
• 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
• Class-Weighted Convolutional Features for Image Retrieval
• Towards Good Practices for Image Retrieval Based on CNN Features
• 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, code, BMVC 2018.
• Detect-to-Retrieve: Efficient Regional Aggregation for Image Search, arxiv.
• 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)

• R2D2: Reliable and Repeatable Detector and Descriptor, R2D2, NeurIPS 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, hardnet
• MatchNet: Unifying Feature and Metric Learning for Patch-Based Matching, matchnet
• 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.
• 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.

ANN search

• 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.
• 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 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.
• Web-Scale Responsive Visual Search at Bing
• Visual Search at Alibaba
• Visual Search at Pinterest
• Visual Discovery at Pinterest
• 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

CBIR Competition and Challenge

• 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 Robust and Fast Video Copy Detection System Using Content-Based Fingerprinting

Feature Fusion

• Feature fusion using Canonical Correlation Analysis

Instance Matching

• 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

• End-to-end weakly-supervised semantic alignment

Image Identification

• Image Identification Using SIFT Algorithm: Performance Analysis against Different Image Deformations

Tutorials

• 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.

Useful Package

• VLFeat
• Yael