awesome-local-global-descriptor
This is my personal note about local and global descriptor. Trying to make anyone can get in to these fields more easily.
If you find anything you want to add, feel free to post on issue or email me.
This repo is also a side product when I was doing the survey of our paper UR2KID. If you find this repo useful, please also consider to cite our paper.
@article{yang2020ur2kid,
title={UR2KiD: Unifying Retrieval, Keypoint Detection, and Keypoint Description without Local Correspondence Supervision},
author={Yang*, Tsun-Yi; Nguyen*, Duy-Kien; Heijnen, Huub; Balntas, Vassileios},
journal={arXiv preprint arXiv:2001.07252},
year={2020}
}
This repo will be constantly updated.
Author: Tsun-Yi Yang (shamangary@hotmail.com )
In this section, I focus on the review about the sparse keypoint matching and it's pipeline.
This subsection includes the review about keypoint detection and it's orientation, scale, or affine transformation estimation.
Year
Paper
link
Code
[ICCV19]
Key.Net: Keypoint Detection by Handcrafted and Learned CNN Filters
PDF
Github
[ECCV18]
Repeatability Is Not Enough: Learning Discriminative Affine Regions via Discriminability
arXiv
Github
[CVPR17]
Learning Discriminative and Transformation Covariant Local Feature Detectors
PDF
Github
[CVPR17]
Quad-networks: unsupervised learning to rank for interest point detection
PDF
-
[CVPR16]
Learning to Assign Orientations to Feature Poitns
-
Github
[CVPR15]
TILDE: a Temporally Invariant Learned DEtector
arXiv
Github
Year
Paper
link
Code
[ICCV19]
USIP: Unsupervised Stable Interest Point Detection from 3D Point Clouds
arXiv
Github
[arXiv19]
Self-Supervised 3D Keypoint Learning for Ego-motion Estimation
arXiv
Github
2. Keypoint description (local descriptor)
In the last few decades, people focus on the patch descriptor
Year
Paper
link
Code
[CVPR16]
Accumulated Stability Voting: A Robust Descriptor from Descriptors of Multiple Scales
PDF
Github
[CVPR15]
Domain-Size Pooling in Local Descriptors: DSP-SIFT
PDF
-
[CVPR15]
BOLD - Binary Online Learned Descriptor For Efficient Image Matching
PDF
Github
[CVPR13]
Boosting binary keypoint descriptors
-
-
[CVPR12]
Freak: Fast retina keypoint
-
-
[CVPR12]
Three things everyone should know to improve object retrieval
PDF
-
[IPOL11]
ASIFT: An Algorithm for Fully Affine Invariant Comparison
-
-
[ICCV11]
BRISK: Binary robust invariant scalable keypoints
-
-
[ICCV11]
Orb: An efficient alternative to sift or surf
-
-
[ICCV11]
Local inten-sity order pattern for feature description
-
-
[CVIU06]
Speeded-up robust features (SURF)
-
-
[ECCV06]
Surf:Speeded up robust features
-
-
[IJCV04]
Distinctive image features from scale-invariant keypoints
-
Github
Year
Paper
link
Code
[TIP19]
Learning Local Descriptors by Optimizing the Keypoint-Correspondence Criterion: Applications to Face Matching, Learning from Unlabeled Videos and 3D-Shape Retrieval
arXiv
Github
[ICCV19]
Beyond Cartesian Representations for Local Descriptors
PDF
-
[CVPR19]
SOSNet: Second Order Similarity Regularization for Local Descriptor Learning
arXiv ,Page
Github
[ECCV18]
GeoDesc: Learning Local Descriptors by Integrating Geometry Constraints
-
Github
[CVPR18]
Local Descriptors Optimized for Average Precision
Page
-
[NIPS17]
Working hard to know your neighbor's margins: Local descriptor learning loss
arXiv
Github
[ICCV17]
DeepCD: Learning Deep Complementary Descriptors for Patch Representations
PDF
Github
[CVPR17]
L2-Net: Deep Learning of Discriminative Patch Descriptor in Euclidean Space
PDF
Github
[arXiv16]
PN-Net: Conjoined Triple Deep Network for Learning Local Image Descriptors
arXiv
Github
[BMVC16]
Learning local feature descriptors with triplets and shallow convolutional neural networks
PDF
Github
[ICCV15]
Discriminative Learning of Deep Convolutional Feature Point Descriptors
Page
Github
[CVPR15]
MatchNet: Unifying Feature and Metric Learning for Patch-Based Matching
PDF
-
[CVPR15]
Learning to compare image patches via convolutional neural networks
PDF
Github
Year
Paper
link
Code
[arXiv19]
DEEPPOINT3D: LEARNING DISCRIMINATIVE LOCAL DESCRIPTORS USING DEEP METRIC LEARNING ON 3D POINT CLOUDS
arXiv
-
3. End-to-end matching pipeline
Recently, more and more papers try to embed the whole matching pipeline (keypoint detection, keypoint description) into one framework.
Year
Paper
link
Code
[CVPR20]
ASLFeat: Learning Local Features of Accurate Shape and Localization
arXiv
github ,tfmatch
[CVPR20]
Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task
arXiv
-
[NIPS19]
R2D2: Repeatable and Reliable Detector and Descriptor
arXiv ,Page
Github
[ICCV19]
ELF: Embedded Localisation of Features in Pre-Trained CNN
PDF
Github
[CVPR19]
RF-Net: An End-to-End Image Matching Network based on Receptive Field
arXiv
Github
[CVPR19]
D2-Net: A Trainable CNN for Joint Description and Detection of Local Features
arXiv ,Page
Github
[CVPRW18]
SuperPoint: Self-Supervised Interest Point Detection and Description
arXiv
Github ,3rd_party
[NIPS18]
LF-Net: Learning Local Features from Images
PDF
Github
[ECCV16]
LIFT: Learned Invariant Feature Points
-
Github
Year
Paper
link
Code
[arXiv20]
StickyPillars: Robust feature matching on point clouds using Graph Neural Networks
arXiv
-
Unlike local keypoint descriptor depends on keypoint, some works try to get the whole dense descriptor representation.
Year
Paper
link
Code
[ICRA20]
GN-Net: The Gauss-Newton Loss for Multi-Weather Relocalization
arXiv , MyNote
Web
[ICCV17]
CLKN: Cascaded Lucas-Kanade Networks for Image Alignment
PDF
-
4. Geometric verification or learning based matcher
After the matching, standard RANSAC and it's variants are usually adopted for outlier removal.
Year
Paper
link
Code
[arXiv20]
Multi-View Optimization of Local Feature Geometry
arXiv
-
[CVPR19]
MAGSAC: Marginalizing Sample Consensus
PDF
Github
[ECCV12]
Improving Image-Based Localization by Active Correspondence Search
PDF
-
[CVPR05]
Matching with PROSAC – Progressive Sample Consensus
PDF
-
[CVPR05]
Two-View Geometry Estimation Unaffected by a Dominant Plane
PDF
Github
Year
Paper
link
Code
[arXiv20]
RANSAC-Flow: generic two-stage image alignment
arXiv
page ,Github
[arXiv19]
SuperGlue: Learning Feature Matching with Graph Neural Networks
arXiv
Github
[ICCV19]
NG-RANSAC for Epipolar Geometry from Sparse Correspondences
arXiv
Github
[ICCV19]
Learning Two-View Correspondences and Geometry Using Order-Aware Network
arXiv
Github
[CVPR18]
Learning to Find Good Correspondences
-
Github
Year
Paper
link
Code
[Access18]
Multi-Temporal Remote Sensing Image Registration Using Deep Convolutional Features
PDF
Github
Consider global retrieval usually targets on a lot of candidates, there are several way to generate one single description for one image.
When there is only hand-crafted local descriptors, people usually uses feature aggregation from a set of local descriptors and output a single description.
Year
Paper
link
Code
[ICCV13] [IJCV15]
To aggregate or not to aggregate: Selective match kernels for image search Image search with selective match kernels: aggregation across single and multiple images
ICCV IJCV
Official : matlab , from DELF (tensorflow)
[CVPR13]
All about VLAD
PDF
-
[ECCV10]
Improving the fisher kernel for large-scale image classification
PDF
-
[CVPR07]
Object retrieval with large vocabularies and fast spatial matching
PDF
-
[CVPR06]
Fisher kenrels on visual vocabularies for image categorizaton
PDF
-
Similar idea but use deep learning to adapt classical algorithm
Year
Paper
link
Code
[ECCV16]
CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples.
PDF
-
[CVPR16]
NetVLAD: CNN architecture for weakly supervised place recognition
Page
Github
2. Real-valued descriptor
One single representation from the image.
Year
Paper
link
Code
[arXiv20]
SOLAR: Second-Order Loss and Attention for Image Retrieval
arXiv
-
[arXiv20]
Unifying Deep Local and Global Features for Efficient Image Search
arXiv
-
[arXiv19]
ACTNET: end-to-end learning of feature activations and multi-stream aggregation for effective instance image retrieval
arXiv
-
[TIP19]
REMAP: Multi-layer entropy-guided pooling of dense CNN features for image retrieval
arXiv
-
[ICCV19]
Learning with Average Precision: Training Image Retrieval with a Listwise Loss
arXiv
Github
[CVPR19]
Detect-to-Retrieve: Efficient Regional Aggregation for Image Search
PDF
Github
[TPAMI18]
Fine-tuning CNN Image Retrieval with No Human Annotation
arXiv
Github
[IJCV17]
End-to-end Learning of Deep Visual Representations for Image Retrieval
arXiv
Github
[ICCV17]
Large-Scale Image Retrieval with Attentive Deep Local Features
-
Github
[ECCV16]
CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples
arXiv
Github
3. Binary descriptor and quantization
For more compact representation, a binary descriptor can be generated from hashing or thresholding. Quantization is also very popular in large-scale image retrieval.
Year
Paper
link
Code
[ICCVW19]
DAME WEB: DynAmic MEan with Whitening Ensemble Binarization for Landmark Retrieval without Human Annotation
PDF
Github
[CVPR19]
FastAP: Deep Metric Learning to Rank
PDF
Github
[CVPR18]
Hashing as Tie-Aware Learning to Rank
PDF
Github
[AAAI18]
Deep Region Hashing for Generic Instance Search from Image
-
-
[TPAMI18]
Supervised Learning of Semantics-Preserving Hash via Deep Convolutional NeuralNetworks
-
-
[TPAMI13]
Iterative Quantization: A Procrustean Approach to Learning Binary Codes for Large-Scale Image Retrieval
PDF
-
[TPAMI10]
Product quantization for nearest neighbor search
PDF
-
Anything can boost the performance in the post-processing stage such as re-ranking or query expansion.
Year
Paper
link
Code
[CVPR19]
Local features and visual words emerge in activations
PDF
-
[CVPR12]
Object retrieval and localization with spatially-constrained similarity measure and k-NN re-ranking
PDF
-
Year
Paper
link
Code
[CVPR18]
PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition
arXiv
Github
Multi-tasking local and global descriptors
Some works try to cover both local descriptor and global retrieval due to the shared similarity about the activation and the applications.
Year
Paper
link
Code
[arXiv20]
UR2KiD: Unifying Retrieval, Keypoint Detection, and Keypoint Description without Local Correspondence Supervision
arXiv
-
[CVPR19]
ContextDesc: Local Descriptor Augmentation with Cross-Modality Context
-
Github
[CVPR19]
From Coarse to Fine: Robust Hierarchical Localization at Large Scale with HF-Net
arXiv
Github
[ICCV17]
Large-Scale Image Retrieval with Attentive Deep Local Features (DELF)
-
Github
Year
Paper
link
Code
[arXiv18]
From handcrafted to deep local features
arXiv
-
[CVPR17]
Comparative Evaluation of Hand-Crafted and Learned Local Features
PDF
-
Year
Paper
link
Code
Note
[arXiv2020]
Image Matching across Wide Baselines: From Paper to Practice
arXiv
github
[CVPR17]
HPatches: A benchmark and evaluation of handcrafted and learned local descriptors
arXiv
Github
Hpatches
[TPAMI11]
Discriminative learning of local image descriptors
Page
-
UBC/Brown dataset (subsets:Liberty (New York), Notre Dame (Paris) and Half Dome (Yosemite))
[CVPR08]
On Benchmarking Camera Calibration and MultiView Stereo for High Resolution Imagery
Year
Paper
link
Code
Note
[CVPR18]
Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking
Page
Github
ROxford5k, RParis6k
[CVPR07]
Object retrieval with large vocabularies and fast spatial matching
Page
-
Oxford5k
[CVPR08]
Lost in Quantization: Improving Particular Object Retrieval in Large Scale Image Databases
Page
-
Paris6k
Localization (both local matching and global retrieval)
Year
Paper
link
Code
Note
[CVPR18]
Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions
PDF ,Page
Github
Aachen-day-night, Robotcar, CMU-seasons