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Found 4 papers, 1 papers with code
A Decoupled Learning Scheme for Real-world Burst Denoising from Raw Images
On one hand, most of the models are trained on video sequences with synthetic noise.
Structure Aggregation for Cross-Spectral Stereo Image Guided Denoising
Instead of aligning the input images via conventional stereo matching, we aggregate structures from the guidance image to estimate a clean structure map for the noisy target image, which is then used to regress the final denoising result with a spatially variant linear representation model.
Aggregating Feature Point Cloud for Depth Completion
We extract 2D feature map from images and transform the sparse depth map to point cloud to extract sparse 3D features.
Guided Colorization Using Mono-Color Image Pairs
Experimental results show that, our algorithm can efficiently restore color images with higher SNR and richer details from the mono-color image pairs, and achieves good performance in solving the color bleeding problem.
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