# ALIKE: Accurate and Lightweight Keypoint Detection and Descriptor Extraction

arXiv: https://arxiv.org/abs/2112.02906 · HTML: https://mlsanity.com/paper/2112.02906/

## Key facts

- Cited by 77 papers in the map (data through 14 Oct 2026).
- Builds on 31 of its 52 references that are in the map.
- First posted on arXiv 6 Dec 2021.

## Builds on (most cited first, 30 of 31)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [SuperPoint: Self-Supervised Interest Point Detection and Description](https://mlsanity.com/paper/1712.07629/) (2017)
- [ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras](https://mlsanity.com/paper/1610.06475/) (2016)
- [MegaDepth: Learning Single-View Depth Prediction from Internet Photos](https://mlsanity.com/paper/1804.00607/) (2018)
- [D2-Net: A Trainable CNN for Joint Detection and Description of Local Features](https://mlsanity.com/paper/1905.03561/) (2019)
- [DISK: Learning local features with policy gradient](https://mlsanity.com/paper/2006.13566/) (2020)
- [LIFT: Learned Invariant Feature Transform](https://mlsanity.com/paper/1603.09114/) (2016)
- [HPatches: A benchmark and evaluation of handcrafted and learned local descriptors](https://mlsanity.com/paper/1704.05939/) (2017)
- [Integral Human Pose Regression](https://mlsanity.com/paper/1711.08229/) (2017)
- [Image Matching across Wide Baselines: From Paper to Practice](https://mlsanity.com/paper/2003.01587/) (2020)
- [Working hard to know your neighbor's margins: Local descriptor learning loss](https://mlsanity.com/paper/1705.10872/) (2017)
- [R2D2: Repeatable and Reliable Detector and Descriptor](https://mlsanity.com/paper/1906.06195/) (2019)
- [LF-Net: Learning Local Features from Images](https://mlsanity.com/paper/1805.09662/) (2018)
- [SOSNet: Second Order Similarity Regularization for Local Descriptor Learning](https://mlsanity.com/paper/1904.05019/) (2019)
- [ASLFeat: Learning Local Features of Accurate Shape and Localization](https://mlsanity.com/paper/2003.10071/) (2020)
- [Key.Net: Keypoint Detection by Handcrafted and Learned CNN Filters](https://mlsanity.com/paper/1904.00889/) (2019)
- [Learning Feature Descriptors using Camera Pose Supervision](https://mlsanity.com/paper/2004.13324/) (2020)
- [VPR-Bench: An Open-Source Visual Place Recognition Evaluation Framework with Quantifiable Viewpoint and Appearance Change](https://mlsanity.com/paper/2005.08135/) (2020)
- [TILDE: A Temporally Invariant Learned DEtector](https://mlsanity.com/paper/1411.4568/) (2014)
- [Local Descriptors Optimized for Average Precision](https://mlsanity.com/paper/1804.05312/) (2018)
- [Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task](https://mlsanity.com/paper/1912.00623/) (2019)
- [Quad-networks: unsupervised learning to rank for interest point detection](https://mlsanity.com/paper/1611.07571/) (2016)
- [D2D: Keypoint Extraction with Describe to Detect Approach](https://mlsanity.com/paper/2005.13605/) (2020)
- [S2DNet: Learning Accurate Correspondences for Sparse-to-Dense Feature Matching](https://mlsanity.com/paper/2004.01673/) (2020)
- [Sparse-to-Dense Hypercolumn Matching for Long-Term Visual Localization](https://mlsanity.com/paper/1907.03965/) (2019)
- [UR2KiD: Unifying Retrieval, Keypoint Detection, and Keypoint Description without Local Correspondence Supervision](https://mlsanity.com/paper/2001.07252/) (2020)
- [Neural Reprojection Error: Merging Feature Learning and Camera Pose Estimation](https://mlsanity.com/paper/2103.07153/) (2021)
- [HDD-Net: Hybrid Detector Descriptor with Mutual Interactive Learning](https://mlsanity.com/paper/2005.05777/) (2020)
- [SEKD: Self-Evolving Keypoint Detection and Description](https://mlsanity.com/paper/2006.05077/) (2020)

## Built on by (most cited first, 30 of 77)

- [ALIKED: A Lighter Keypoint and Descriptor Extraction Network via Deformable Transformation](https://mlsanity.com/paper/2304.03608/) (2023)
- [XFeat: Accelerated Features for Lightweight Image Matching](https://mlsanity.com/paper/2404.19174/) (2024)
- [DeDoDe: Detect, Don't Describe -- Describe, Don't Detect for Local Feature Matching](https://mlsanity.com/paper/2308.08479/) (2023)
- [DeDoDe v2: Analyzing and Improving the DeDoDe Keypoint Detector](https://mlsanity.com/paper/2404.08928/) (2024)
- [Local Feature Matching Using Deep Learning: A Survey](https://mlsanity.com/paper/2401.17592/) (2024)
- [MESA: Matching Everything by Segmenting Anything](https://mlsanity.com/paper/2401.16741/) (2024)
- [Segment Anything Model is a Good Teacher for Local Feature Learning](https://mlsanity.com/paper/2309.16992/) (2023)
- [EarthMatch: Iterative Coregistration for Fine-grained Localization of Astronaut Photography](https://mlsanity.com/paper/2405.05422/) (2024)
- [Learning to Make Keypoints Sub-Pixel Accurate](https://mlsanity.com/paper/2407.11668/) (2024)
- [DaD: Distilled Reinforcement Learning for Diverse Keypoint Detection](https://mlsanity.com/paper/2503.07347/) (2025)
- [RDD: Robust Feature Detector and Descriptor using Deformable Transformer](https://mlsanity.com/paper/2505.08013/) (2025)
- [LiftFeat: 3D Geometry-Aware Local Feature Matching](https://mlsanity.com/paper/2505.03422/) (2025)
- [LoMa: Local Feature Matching Revisited](https://mlsanity.com/paper/2604.04931/) (2026)
- [FeatureBooster: Boosting Feature Descriptors with a Lightweight Neural Network](https://mlsanity.com/paper/2211.15069/) (2022)
- [Searching from Area to Point: A Hierarchical Framework for Semantic-Geometric Combined Feature Matching](https://mlsanity.com/paper/2305.00194/) (2023)
- [A Guide to Structureless Visual Localization](https://mlsanity.com/paper/2504.17636/) (2025)
- [3MOS: Multi-sources, Multi-resolutions, and Multi-scenes dataset for Optical-SAR image matching](https://mlsanity.com/paper/2404.00838/) (2024)
- [Multi-modal Retinal Image Registration Using a Keypoint-Based Vessel Structure Aligning Network](https://mlsanity.com/paper/2207.10506/) (2022)
- [OAMatcher: An Overlapping Areas-based Network for Accurate Local Feature Matching](https://mlsanity.com/paper/2302.05846/) (2023)
- [EDM: Efficient Deep Feature Matching](https://mlsanity.com/paper/2503.05122/) (2025)
- [Deep Learning Reforms Image Matching: A Survey and Outlook](https://mlsanity.com/paper/2506.04619/) (2025)
- [Affine steerers for structured keypoint description](https://mlsanity.com/paper/2408.14186/) (2024)
- [MIFNet: Learning Modality-Invariant Features for Generalizable Multimodal Image Matching](https://mlsanity.com/paper/2501.11299/) (2025)
- [SRPose: Two-view Relative Pose Estimation with Sparse Keypoints](https://mlsanity.com/paper/2407.08199/) (2024)
- [Leveraging Semantic Cues from Foundation Vision Models for Enhanced Local Feature Correspondence](https://mlsanity.com/paper/2410.09533/) (2024)
- [Image Matching Filtering and Refinement by Planes and Beyond](https://mlsanity.com/paper/2411.09484/) (2024)
- [Breaking of brightness consistency in optical flow with a lightweight CNN network](https://mlsanity.com/paper/2310.15655/) (2023)
- [Mismatched: Evaluating the Limits of Image Matching Approaches and Benchmarks](https://mlsanity.com/paper/2408.16445/) (2024)
- [Keypoint Detection and Description for Raw Bayer Images](https://mlsanity.com/paper/2503.08673/) (2025)
- [MESA: Effective Matching Redundancy Reduction by Semantic Area Segmentation](https://mlsanity.com/paper/2408.00279/) (2024)

## Abstract (arXiv)

Existing methods detect the keypoints in a non-differentiable way, therefore they can not directly optimize the position of keypoints through back-propagation. To address this issue, we present a partially differentiable keypoint detection module, which outputs accurate sub-pixel keypoints. The reprojection loss is then proposed to directly optimize these sub-pixel keypoints, and the dispersity peak loss is presented for accurate keypoints regularization. We also extract the descriptors in a sub-pixel way, and they are trained with the stable neural reprojection error loss. Moreover, a lightweight network is designed for keypoint detection and descriptor extraction, which can run at 95 frames per second for 640x480 images on a commercial GPU. On homography estimation, camera pose estimation, and visual (re-)localization tasks, the proposed method achieves equivalent performance with the state-of-the-art approaches, while greatly reduces the inference time.