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Found 3 papers, 3 papers with code
Evaluating the Faithfulness of Saliency-based Explanations for Deep Learning Models for Temporal Colour Constancy
The opacity of deep learning models constrains their debugging and improvement.
Cascading Convolutional Temporal Colour Constancy
We extend this architecture with different models obtained by (i) substituting the TCCNet submodules with C4, the state-of-the-art method for CCC targeting images; (ii) adding a cascading strategy to perform an iterative improvement of the estimate of the illuminant.
Contextual Residual Aggregation for Ultra High-Resolution Image Inpainting
Since convolutional layers of the neural network only need to operate on low-resolution inputs and outputs, the cost of memory and computing power is thus well suppressed.
Ranked #6 on
Image Inpainting
on Places2 val
