Vision Transformers for Single Image Specular Highlight Detection
Abstract: Specular highlight detection is a useful task influencing applications such as image analysis and scene understanding. This study investigates using a multi-scale patch-based selfattention mechanism in a deep neural network model for specular highlight detection. Multi-scale patch-based self-attention enhances the model’s ability to capture intricate patterns and global dependencies. The proposed method produces highly accurate results on real images with complex specular highlights and is highly competitive with state-of-the-art methods.
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