3260 papers • 126 benchmarks • 313 datasets
Multimodal patch matching focuses on matching patches originating from different sources, such as visible RGB and near-infrared.
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This work proposes a three-stream architecture, dubbed as TS-Net, combining the benefits of the Siamese and Pseudo-Siamese networks, and shows that adding extra constraints in the intermediate layers of such networks further boosts the performance.
This work proposes an attention-based approach for multimodal image patch matching using a Transformer encoder attending to the feature maps of a multiscale Siamese CNN, and introduces an attentionresidual architecture, using a residual connection bypassing the encoder.
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