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Found 3 papers, 3 papers with code
Image Inpainting with Edge-guided Learnable Bidirectional Attention Maps
In this paper, we present an edge-guided learnable bidirectional attention map (Edge-LBAM) for improving image inpainting of irregular holes with several distinct merits.
Learning Class-Agnostic Pseudo Mask Generation for Box-Supervised Semantic Segmentation
For learning pseudo mask generator from the auxiliary dataset, we present a bi-level optimization formulation.
Image Inpainting with Learnable Bidirectional Attention Maps
Most convolutional network (CNN)-based inpainting methods adopt standard convolution to indistinguishably treat valid pixels and holes, making them limited in handling irregular holes and more likely to generate inpainting results with color discrepancy and blurriness.
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Image Inpainting
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