
The core message of this paper is that the domain gap in Heterogeneous Face Recognition (HFR) can be effectively addressed by conceptualizing different modalities as distinct styles and employing a Conditional Adaptive Instance Modulation (CAIM) module to seamlessly adapt the intermediate feature maps of a pre-trained face recognition network.


coremsg

bridging-the-domain-gap-in-heterogeneous-face-recognition-through-conditional-adaptive-instance-modulation


Bridging the Domain Gap in Heterogeneous Face Recognition through Conditional Adaptive Instance Modulation


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A novel approach for learning domain-invariant layers called Domain-Invariant Units (DIU) to enhance pretrained face recognition models for the task of heterogeneous face recognition.


enhancing-pretrained-face-recognition-models-for-heterogeneous-face-matching-using-domain-invariant-units


Enhancing Pretrained Face Recognition Models for Heterogeneous Face Matching Using Domain-Invariant Units
