Results 11 to 20 of about 3,367,886 (347)
Robust Feature Matching with Spatial Smoothness Constraints
Remote Sensing, 2020 Feature matching is to detect and match corresponding feature points in stereo pairs, which is one of the key techniques in accurate camera orientations.
Xu Huang, Xue Wan, Daifeng Peng
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Robust Line Feature Matching via Point–Line Invariants and Geometric Constraints [PDF]
SensorsLine feature matching is a crucial aspect of computer vision and image processing tasks, attracting significant research attention. Most line matching algorithms predominantly rely on local feature descriptors or deep learning modules, which often suffer
Chenyang Zhang +5 more
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A Fast Dense Feature-Matching Model for Cross-Track Pushbroom Satellite Imagery [PDF]
Sensors, 2018 Feature-based matching can provide high robust correspondences and it is usually invariant to image scale and rotation. Nevertheless, in remote sensing, the robust feature-matching algorithms often require costly computations for matching dense features ...
Wen-Liang Du +3 more
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AMatFormer: Efficient Feature Matching via Anchor Matching Transformer [PDF]
IEEE transactions on multimedia, 2023 Learning based feature matching methods have been commonly studied in recent years. The core issue for learning feature matching is to how to learn (1) discriminative representations for feature points (or regions) within each intra-image and (2 ...
Bo Jiang +4 more
semanticscholar +3 more sources
Structured Epipolar Matcher for Local Feature Matching [PDF]
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023 Local feature matching is challenging due to textureless and repetitive patterns. Existing methods focus on using appearance features and global interaction and matching, while the importance of geometry priors in local feature matching has not been ...
Jiahao Chang, Jiahuan Yu, Tianzhu Zhang
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LoFTR: Detector-Free Local Feature Matching with Transformers [PDF]
Computer Vision and Pattern Recognition, 2021 We present a novel method for local image feature matching. Instead of performing image feature detection, description, and matching sequentially, we propose to first establish pixel-wise dense matches at a coarse level and later refine the good matches ...
Jiaming Sun +4 more
semanticscholar +1 more source
LightGlue: Local Feature Matching at Light Speed [PDF]
IEEE International Conference on Computer Vision, 2023 We introduce LightGlue, a deep neural network that learns to match local features across images. We revisit multiple design decisions of SuperGlue, the state of the art in sparse matching, and derive simple but effective improvements.
Philipp Lindenberger +2 more
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RoMa: Robust Dense Feature Matching [PDF]
Computer Vision and Pattern Recognition, 2023 Feature matching is an important computer vision task that involves estimating correspondences between two images of a 3D scene, and dense methods estimate all such correspondences.
Johan Edstedt +4 more
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Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching [PDF]
International Conference on Learning Representations, 2023 Powered by large-scale pre-training, vision foundation models exhibit significant potential in open-world image understanding. However, unlike large language models that excel at directly tackling various language tasks, vision foundation models require ...
Yang Liu +5 more
semanticscholar +1 more source
Stereo Matching Network with Multi-Cost Fusion [PDF]
Jisuanji gongcheng, 2022 In stereo matching networks, the feature extraction process is key for improving the accuracy of binocular stereo matching.To extract image feature information, this study combines the characteristics of dense atrous convolution, spatial pyramid pooling,
ZHANG Xiying, WANG Houbo, BIAN Jilong
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