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The document presents a novel end-to-end architecture for facial expression recognition (FER) that utilizes a spatio-channel attention net (SCAN) and a complementary context information (CCI) branch, enhancing robustness against occlusions and pose variations without relying on landmark detectors. The proposed model demonstrates superior performance on various datasets, including in-lab and in-the-wild scenarios, and addresses limitations of existing attention-based CNNs in FER. The architecture incorporate

Author

Dhiraj Bhandari

Language

EN