Feb. 12, 2024, 5:45 a.m. | Maitreya Suin Kuldeep Purohit A. N. Rajagopalan

cs.CV updates on arXiv.org arxiv.org

This paper tackles the problem of motion deblurring of dynamic scenes. Although end-to-end fully convolutional designs have recently advanced the state-of-the-art in non-uniform motion deblurring, their performance-complexity trade-off is still sub-optimal. Most existing approaches achieve a large receptive field by increasing the number of generic convolution layers and kernel size. In this work, we propose a pixel adaptive and feature attentive design for handling large blur variations across different spatial locations and process each test image adaptively. We design a …

advanced art complexity convolution cs.cv designs dynamic hierarchical kernel network paper performance sampling state trade trade-off uniform

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