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RePFormer: Refinement Pyramid Transformer for Robust Facial Landmark Detection
2022
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence
unpublished
This paper presents a Refinement Pyramid Transformer (RePFormer) for robust facial landmark detection. Most facial landmark detectors focus on learning representative image features. However, these CNN-based feature representations are not robust enough to handle complex real-world scenarios due to ignoring the internal structure of landmarks, as well as the relations between landmarks and context. In this work, we formulate the facial landmark detection task as refining landmark queries along
doi:10.24963/ijcai.2022/149
fatcat:zgcs7o7xjvg7lgahwynysg52xa