SuperPoint: Self-Supervised Interest Point Detection and Description
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- Type
- preprint
- Published
- 2017-12-20
- Cited by
- 3,665
- References
- 34
- Access
- Open access
- OpenAlex
- https://openalex.org/W2775929773
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:4918026
Keywords
Interest point detection, Scale-invariant feature transform, Computer science, Artificial intelligence, Boosting (machine learning)
References
- Evaluation of Interest Point Detectors
- Multiple View Geometry in Computer Vision
- ORB-SLAM: A Versatile and Accurate Monocular SLAM System
- Very Deep Convolutional Networks for Large-Scale Image Recognition
- Discriminative Learning of Deep Convolutional Feature Point Descriptors
- SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
- TILDE: A Temporally Invariant Learned DEtector
- A Combined Corner and Edge Detector
- ORB: An efficient alternative to SIFT or SURF
- Good features to track
- Distinctive Image Features from Scale-Invariant Keypoints
- Caffe: Convolutional Architecture for Fast Feature Embedding
- Convolutional Pose Machines
- Deep Image Homography Estimation
- Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
- Deconvolution and Checkerboard Artifacts
- Quad-Networks: Unsupervised Learning to Rank for Interest Point Detection
- DeMoN: Depth and Motion Network for Learning Monocular Stereo
- RoomNet: End-to-End Room Layout Estimation
- Convolutional Neural Network Architecture for Geometric Matching
Cited by
- Learning how to be robust: Deep polynomial regression
- SIPS: Unsupervised Succinct Interest Points
- On Machine Learning and Structure for Mobile Robots
- From handcrafted to deep local invariant features
- Deep Spectral Correspondence for Matching Disparate Image Pairs
- Leveraging Deep Visual Descriptors for Hierarchical Efficient Localization
- Interest point detectors stability evaluation on ApolloScape dataset
- Deep Fundamental Matrix Estimation without Correspondences
- Matching Disparate Image Pairs Using Shape-Aware ConvNets
- Hybrid Camera Array-Based UAV Auto-Landing on Moving UGV in GPS-Denied Environment
- MIST: Multiple Instance Spatial Transformer Network
- Matching Features without Descriptors: Implicitly Matched Interest Points
- From Coarse to Fine: Robust Hierarchical Localization at Large Scale
- Self-Improving Visual Odometry
- Flow Based Self-supervised Pixel Embedding for Image Segmentation
- DF-SLAM: A Deep-Learning Enhanced Visual SLAM System based on Deep Local Features
- Robust RGB-D odometry under depth uncertainty for structured environments.
- Speed Invariant Time Surface for Learning to Detect Corner Points With Event-Based Cameras
- Geometric Image Correspondence Verification by Dense Pixel Matching
- Mismatch Removal for Remote Sensing Images Based on Non-Rigid Transformation and Local Geometrical Constraint
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- ORB: An efficient alternative to SIFT or SURF
- Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
- TILDE: A Temporally Invariant Learned DEtector
- Very Deep Convolutional Networks for Large-Scale Image Recognition