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library_name: pytorch

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RetinaFace is a state-of-the-art single-stage face detector that combines a robust backbone with multi-task learning to predict face locations, landmarks, and context-aware features simultaneously.

Original paper: RetinaFace: Single-Shot Multi-Level Face Localisation in the Wild

RetinaFace-Resnet50

This model uses RetinaFace with a ResNet-50 backbone, providing a strong trade-off between detection accuracy and computational efficiency. It is well suited for face detection and landmark localization in applications such as authentication, video surveillance, and human–computer interaction.

Model Configuration:

Model Device compression Model Link
RetinaFace-Resnet50 N1-655 Amba_optimized Model_Link
RetinaFace-Resnet50 N1-655 Activation_fp16 Model_Link
RetinaFace-Resnet50 CV7 Amba_optimized Model_Link
RetinaFace-Resnet50 CV7 Activation_fp16 Model_Link
RetinaFace-Resnet50 CV72 Amba_optimized Model_Link
RetinaFace-Resnet50 CV72 Activation_fp16 Model_Link
RetinaFace-Resnet50 CV75 Amba_optimized Model_Link
RetinaFace-Resnet50 CV75 Activation_fp16 Model_Link