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awesome-cbir-papers
📝Awesome and classical image retrieval papers
https://github.com/willard-yuan/awesome-cbir-papers
- 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 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
- Online Invariance Selection for Local Feature Descriptors
- 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
- Deep Image Retrieval:Learning Global Representations for Image search
- End-to-end Learning of Deep Visual Representations for Image retrieval
- What Is the Best Practice for CNNs Applied to Visual Instance Retrieval?
- Bags of Local Convolutional Features for Scalable Instance Search
- Faster R-CNN Features for Instance Search
- Cross-dimensional Weighting for Aggregated Deep Convolutional Features
- Class-Weighted Convolutional Features for Image Retrieval
- Aggregating Deep Convolutional Features for Image Retrieval
- Particular object retrieval with integral max-pooling of CNN activations
- 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
- Selective Deep Convolutional Features for Image Retrieval
- Class-Weighted 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
- Guided Similarity Separation for Image Retrieval
- code
- code
- 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
- COTR: Correspondence Transformer for Matching Across Images
- Online Invariance Selection for Local Feature Descriptors
- 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
- Combination of Multiple Global Descriptors for Image Retrieval
- Beyond Cartesian Representations for Local Descriptors - epfl/log-polar-descriptors), ICCV 2019.
- R2D2: Reliable and Repeatable Detector and Descriptor
- SOSNet: Second Order Similarity Regularization for Local Descriptor Learning
- Local Features and Visual Words Emerge in Activations
- Explicit Spatial Encoding for Deep Local Descriptors
- Key.Net: Keypoint Detection by Handcrafted and Learned CNN Filters
- 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
- Learning local feature descriptors with triplets and shallow convolutional neural networks
- Deeply Activated Salient Region for Instance Search
- Instance search based on weakly supervised feature learning
- Instance Search via Instance Level Segmentation and Feature Representation
- Unsupervised object discovery for instance recognition
- Faster R-CNN Features for Instance 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
- GGNN: Graph-based GPU Nearest Neighbor Search
- Learning to Route in Similarity Graphs
- pq-fast-scan
- faiss
- Polysemous codes
- Optimized Product Quantization
- lopq
- nns_benchmark
- Optimized Product Quantization
- Falconn
- Annoy
- NMSLIB - 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 - based method.
- 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
- Open Set Adversarial Examples
- Fast Spectral Ranking for Similarity Search - aiki/manifold-diffusion), CVPR 2018.
- 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 Alibaba
- 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？
- 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).
- A Self-Supervised Descriptor for Image Copy Detection - copy-detection).
- A Robust and Fast Video Copy Detection System Using Content-Based Fingerprinting
- Feature fusion using Canonical Correlation Analysis
- Neural- Guided RANSAC: Learning Where to Sample Model Hypotheses
- AdaLAM: Revisiting Handcrafted Outlier Detection
- Graph-Cut RANSAC - cut-ransac)
- 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
- 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 - from-sift-features).
- End-to-end weakly-supervised semantic alignment
- QATM: Quality-Aware Template Matching For Deep Learning
- Image Identification Using SIFT Algorithm: Performance Analysis against Different Image Deformations
- PyRetri
- How to Apply Distance Metric Learning to Street-to-Shop Problem
- Recent Image Search Techniques
- Compact Features for Visual Search
- multimedia-indexing - scale feature extraction, indexing and retrieval.
- Image Similarity using Deep Ranking - similarity-deep-ranking).
- Triplet Loss and Online Triplet Mining in TensorFlow
- tf_retrieval_baseline
- VRG Prague in “Large-Scale Landmark Recognition Challenge”
- Visual Image Retrieval and Localization
- VGG Image Search Engine
- SoTu - based cbir system.
- yisou - based painting cbir system, the search algorithm is designed by [Yong Yuan](http://yongyuan.name/).
- DeepFashion2 Dataset
- Holidays
- Oxford
- Paris
- ROxford and RParis
- INSTRE - level object retrieval dataset.
- VLFeat
- Yael
- ![Star History Chart - history.com/#willard-yuan/awesome-cbir-papers&Date)
Keywords
deep-learning
5
nearest-neighbor-search
5
image-retrieval
4
pytorch
3
locality-sensitive-hashing
2
cbir
2
product-quantization
2
approximate-nearest-neighbor-search
2
cuda
2
gpu
2
computer-vision
2
descriptor
1
tfeat-descriptor
1
triplets
1
ann
1
vector-database
1
vector-db
1
simd
1
clustering
1
lopq
1
spark
1
cam
1
class-activation-maps
1
convolutional-neural-networks
1
keras
1
transfer-learning
1
vgg16
1
visual-instance-search
1
gcn
1
manifold-learning
1
neurips
1
neurips-2019
1
iccv2023
1
image-matching
1
cgd
1
global-descriptor
1
mxnet
1
cosine-similarity
1
cub-dataset
1
deep-neural-networks
1
embedding
1
metric-learning
1
python3
1
retrieval
1
retrieving-images
1
stanford-online
1
tensorflow
1
tensorflow-retrieval
1
tensorflow1
1
tensorflow2
1