Geometric Matching
24 papers with code • 1 benchmarks • 1 datasets
Libraries
Use these libraries to find Geometric Matching models and implementationsMost implemented papers
Convolutional neural network architecture for geometric matching
We address the problem of determining correspondences between two images in agreement with a geometric model such as an affine or thin-plate spline transformation, and estimating its parameters.
Toward Characteristic-Preserving Image-based Virtual Try-On Network
Second, to alleviate boundary artifacts of warped clothes and make the results more realistic, we employ a Try-On Module that learns a composition mask to integrate the warped clothes and the rendered image to ensure smoothness.
Learning Accurate Dense Correspondences and When to Trust Them
Establishing dense correspondences between a pair of images is an important and general problem.
Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks
While such generic features cannot compete with class specific features from supervised training on a classification task, we show that they are advantageous on geometric matching problems, where they also outperform the SIFT descriptor.
GLU-Net: Global-Local Universal Network for Dense Flow and Correspondences
Establishing dense correspondences between a pair of images is an important and general problem, covering geometric matching, optical flow and semantic correspondences.
GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network
We propose GOCor, a fully differentiable dense matching module, acting as a direct replacement to the feature correlation layer.
Correlation Verification for Image Retrieval
Geometric verification is considered a de facto solution for the re-ranking task in image retrieval.
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.
ContextDesc: Local Descriptor Augmentation with Cross-Modality Context
Most existing studies on learning local features focus on the patch-based descriptions of individual keypoints, whereas neglecting the spatial relations established from their keypoint locations.
Self-Supervised 3D Keypoint Learning for Ego-motion Estimation
Detecting and matching robust viewpoint-invariant keypoints is critical for visual SLAM and Structure-from-Motion.