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- W4316143377 abstract "Specular highlight detection is a fundamental research topic in computer graphics and computer vision. In this paper, we present a new full-scale deep supervision model to detect specular highlights from single real-world images. The core of our approach is a novel self-attention module to improve the detection accuracy of the network. We also introduce a refinement strategy with a new loss function for highlight detection task by generating contour maps from the highlight detection masks. Experiments on a public dataset demonstrate that our approach outperforms state-of-the-art methods for highlight detection." @default.
- W4316143377 created "2023-01-14" @default.
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- W4316143377 date "2022-12-27" @default.
- W4316143377 modified "2023-09-26" @default.
- W4316143377 title "Contour-constrained Specular Highlight Detection from Real-world Images" @default.
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- W4316143377 doi "https://doi.org/10.1145/3574131.3574461" @default.
- W4316143377 hasPublicationYear "2022" @default.
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