Patch Matching
32 papers with code • 2 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Patch Matching
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HPatches
VIPeR
ETH SfM
PhotoSynth
Latest papers with no code
Learning to Scale Temperature in Masked Self-Attention for Image Inpainting
Recent advances in deep generative adversarial networks (GAN) and self-attention mechanism have led to significant improvements in the challenging task of inpainting large missing regions in an image.
Large-scale Global Low-rank Optimization for Computational Compressed Imaging
However, the computational cost has inhibited NLR from seeking global structural similarity, which consequentially keeps it trapped in the tradeoff between accuracy and efficiency and prevents it from high-dimensional large-scale tasks.
Compositional Scene Modeling with Global Object-Centric Representations
Inspired by such an ability of humans, this paper proposes a compositional scene modeling method to infer global representations of canonical images of objects without any supervision.
Learned Distributed Image Compression with Multi-Scale Patch Matching in Feature Domain
Specifically, MSFDPM consists of a side information feature extractor, a multi-scale feature domain patch matching module, and a multi-scale feature fusion network.
Forward-Looking Sonar Patch Matching: Modern CNNs, Ensembling, and Uncertainty
Application of underwater robots are on the rise, most of them are dependent on sonar for underwater vision, but the lack of strong perception capabilities limits them in this task.
DivSwapper: Towards Diversified Patch-based Arbitrary Style Transfer
Gram-based and patch-based approaches are two important research lines of style transfer.
Image Denoising by Gaussian Patch Mixture Model and Low Rank Patches
Local patch matching is to find similar patches in a large neighborhood which can alleviate noise effect, but the number of patches may be insufficient.
IF-Net: An Illumination-invariant Feature Network
To show the practicality, we further evaluate IF-Net on the task of visual localization under large illumination changes scenes, and achieves the best localization accuracy.
Explaining Away Results in Accurate and Tolerant Template Matching
In contrast, the method advocated here takes into account the evidence provided by the image for the template at each location and the full range of alternative explanations represented by the same template at other locations and by other templates.
AFD-Net: Aggregated Feature Difference Learning for Cross-Spectral Image Patch Matching
Image patch matching across different spectral domains is more challenging than in a single spectral domain.
