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
Latest papers
Boosting Multi-view Stereo with Late Cost Aggregation
To address this challenge, we present a late aggregation approach that allows for aggregating pairwise costs throughout the network feed-forward process, achieving accurate estimations with only minor changes of the plain CasMVSNet.
Rethinking Optical Flow from Geometric Matching Consistent Perspective
dqiaole/matchflow
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CVPR 2023
In this paper, we propose a rethinking to previous optical flow estimation.
Geometric Visual Similarity Learning in 3D Medical Image Self-supervised Pre-training
yutinghe-list/gvsl
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CVPR 2023
We propose a novel visual similarity learning paradigm, Geometric Visual Similarity Learning, which embeds the prior of topological invariance into the measurement of the inter-image similarity for consistent representation of semantic regions.
C-VTON: Context-Driven Image-Based Virtual Try-On Network
At the core of the C-VTON pipeline are: (i) a geometric matching procedure that efficiently aligns the target clothing with the pose of the person in the input images, and (ii) a powerful image generator that utilizes various types of contextual information when synthesizing the final try-on result.
Correlation Verification for Image Retrieval
Geometric verification is considered a de facto solution for the re-ranking task in image retrieval.
DKM: Dense Kernelized Feature Matching for Geometry Estimation
This changes with our novel dense method, which outperforms both dense and sparse methods on geometry estimation.
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.
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.
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.
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.
