Results 21 to 30 of about 3,909,906 (397)
ParaFormer: Parallel Attention Transformer for Efficient Feature Matching [PDF]
AAAI Conference on Artificial Intelligence, 2023 Heavy computation is a bottleneck limiting deep-learning-based feature matching algorithms to be applied in many real-time applications. However, existing lightweight networks optimized for Euclidean data cannot address classical feature matching tasks ...
Xiaoyong Lu +3 more
semanticscholar +1 more source
DKM: Dense Kernelized Feature Matching for Geometry Estimation [PDF]
Computer Vision and Pattern Recognition, 2022 Feature matching is a challenging computer vision task that involves finding correspondences between two images of a 3D scene. In this paper we consider the dense approach instead of the more common sparse paradigm, thus striving to find all ...
Johan Edstedt +3 more
semanticscholar +1 more source
Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution Priors [PDF]
ACM Multimedia, 2022 A key challenge of real-world image super-resolution (SR) is to recover the missing details in low-resolution (LR) images with complex unknown degradations (\eg, downsampling, noise and compression).
Chaofeng Chen +6 more
semanticscholar +1 more source
ClusterGNN: Cluster-based Coarse-to-Fine Graph Neural Network for Efficient Feature Matching [PDF]
Computer Vision and Pattern Recognition, 2022 Graph Neural Networks (GNNs) with attention have been successfully applied for learning visual feature matching. However, current methods learn with complete graphs, resulting in a quadratic complexity in the number of features.
Yanxing Shi +5 more
semanticscholar +1 more source
DFNet: Enhance Absolute Pose Regression with Direct Feature Matching [PDF]
European Conference on Computer Vision, 2022 We introduce a camera relocalization pipeline that combines absolute pose regression (APR) and direct feature matching. By incorporating exposure-adaptive novel view synthesis, our method successfully addresses photometric distortions in outdoor ...
Shuai Chen +3 more
semanticscholar +1 more source
TopicFM: Robust and Interpretable Topic-Assisted Feature Matching [PDF]
AAAI Conference on Artificial Intelligence, 2022 This study addresses an image-matching problem in challenging cases, such as large scene variations or textureless scenes. To gain robustness to such situations, most previous studies have attempted to encode the global contexts of a scene via graph ...
Khang Truong Giang +2 more
semanticscholar +1 more source
BRIFT: A Binary Descriptor for Multi-Modal Image Registration [PDF]
Hangkong bingqi, 2023 Using radiation-variation insensitivity feature transform (RIFT) to calculate feature descriptors and perform feature matching on the maximum index map (MIM) is time-consuming.
Xu Kaikai, Guo Pengcheng, Wang Jingjing
doaj +1 more source
Adaptive Assignment for Geometry Aware Local Feature Matching [PDF]
Computer Vision and Pattern Recognition, 2022 The detector-free feature matching approaches are currently attracting great attention thanks to their excellent performance. However, these methods still struggle at large-scale and viewpoint variations, due to the geometric inconsistency resulting from
Dihe Huang +7 more
semanticscholar +1 more source
FedFM: Anchor-Based Feature Matching for Data Heterogeneity in Federated Learning [PDF]
IEEE Transactions on Signal Processing, 2022 One of the key challenges in federated learning (FL) is local data distribution heterogeneity across clients, which may cause inconsistent feature spaces across clients.
Rui Ye +5 more
semanticscholar +1 more source
SuperGlue: Learning Feature Matching With Graph Neural Networks [PDF]
Computer Vision and Pattern Recognition, 2019 This paper introduces SuperGlue, a neural network that matches two sets of local features by jointly finding correspondences and rejecting non-matchable points.
Paul-Edouard Sarlin +3 more
semanticscholar +1 more source