Geometric Matching
24 papers with code • 1 benchmarks • 1 datasets
Benchmarks
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Libraries
Use these libraries to find Geometric Matching models and implementations
HPatches
Most implemented papers
SieveNet: A Unified Framework for Robust Image-Based Virtual Try-On
An efficient framework for this is composed of two stages: (1) warping (transforming) the try-on cloth to align with the pose and shape of the target model, and (2) a texture transfer module to seamlessly integrate the warped try-on cloth onto the target model image.
Learning Part Segmentation through Unsupervised Domain Adaptation from Synthetic Vehicles
We believe our dataset provides a rich testbed to study UDA for part segmentation and will help to significantly push forward research in this area.
Spatial Content Alignment For Pose Transfer
Due to unreliable geometric matching and content misalignment, most conventional pose transfer algorithms fail to generate fine-trained person images.
Convolutional Hough Matching Networks
Despite advances in feature representation, leveraging geometric relations is crucial for establishing reliable visual correspondences under large variations of images.
Deep Matching Prior: Test-Time Optimization for Dense Correspondence
Conventional techniques to establish dense correspondences across visually or semantically similar images focused on designing a task-specific matching prior, which is difficult to model.
Object-Augmented RGB-D SLAM for Wide-Disparity Relocalisation
YuhangMing/Object-Guided-Relocalisation
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During the map construction, we use a pre-trained neural network to detect objects and estimate 6D poses from RGB-D data.
Convolutional Hough Matching Networks for Robust and Efficient Visual Correspondence
juhongm999/chm
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To validate the proposed techniques, we develop the neural network with CHM layers that perform convolutional matching in the space of translation and scaling.
PDC-Net+: Enhanced Probabilistic Dense Correspondence Network
In order to apply dense methods to real-world applications, such as pose estimation, image manipulation, or 3D reconstruction, it is therefore crucial to estimate the confidence of the predicted matches.
ScaleNet: A Shallow Architecture for Scale Estimation
axelbarroso/scalenet
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CVPR 2022
We formulate the scale estimation problem as a prediction of a probability distribution over scale factors.
Full Transformer Framework for Robust Point Cloud Registration with Deep Information Interaction
Recent Transformer-based methods have achieved advanced performance in point cloud registration by utilizing advantages of the Transformer in order-invariance and modeling dependency to aggregate information.
