Geometric Image Correspondence Verification by Dense Pixel Matching
Explore this paper's citation graph
- Type
- preprint
- Published
- 2019-04-15
- Cited by
- 13
- References
- 49
- Access
- Open access
- OpenAlex
- https://openalex.org/W2937400751
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:119111398
Keywords
Pixel, Artificial intelligence, Pattern recognition (psychology), Metric (unit), Similarity (geometry)
References
- Fine-Tuning CNN Image Retrieval with No Human Annotation
- Hypercolumns for object segmentation and fine-grained localization
- Learning to compare image patches via convolutional neural networks
- Image Classification with the Fisher Vector: Theory and Practice
- Three things everyone should know to improve object retrieval
- Shady dealings: Robust, long-term visual localisation using illumination invariance
- Aggregating local descriptors into a compact image representation
- Image Retrieval for Image-Based Localization Revisited
- Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
- Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval
- Matching with PROSAC - progressive sample consensus
- ImageNet: A large-scale hierarchical image database
- Video Google: a text retrieval approach to object matching in videos
- A contextual dissimilarity measure for accurate and efficient image search
- Distinctive Image Features from Scale-Invariant Keypoints
- NetVLAD: CNN Architecture for Weakly Supervised Place Recognition
- Optimal Randomized RANSAC with SPRT
- Learning and Calibrating Per-Location Classifiers for Visual Place Recognition
- Structure-from-Motion Revisited
- FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
Cited by
- Analysis and Modeling of the Multi-wavelength Observations of the Luminous GRB 190114C
- KNEEL: Knee Anatomical Landmark Localization Using Hourglass Networks
- GLU-Net: Global-Local Universal Network for Dense Flow and Correspondences
- RANSAC-Flow: generic two-stage image alignment
- Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition
- Digging Into Self-Supervised Learning of Feature Descriptors
- Why-So-Deep: Towards Boosting Previously Trained Models for Visual Place Recognition
- PUMP: Pyramidal and Uniqueness Matching Priors for Unsupervised Learning of Local Descriptors
- ETR: An Efficient Transformer for Re-ranking in Visual Place Recognition
- LMFD: lightweight multi-feature descriptors for image stitching
- GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network
- LCDNet: Deep Loop Closure Detection for LiDAR SLAM based on Unbalanced Optimal Transport
- GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network
- Deep Kernelized Dense Geometric Matching
Related papers
- DGC-Net: Dense Geometric Correspondence Network
- Content-based image retrieval by interest-point matching and geometric hashing
- Exploiting local linear geometric structure for identifying correct matches
- Mismatch Removal for Wide-baseline Image Matching via Coherent Region-to-Region Correspondence
- FlowNet: Learning Optical Flow with Convolutional Networks