Shypd.aiThe largest open index of AI toolsFSA-Net is an open-source research tool for head pose estimation from a single image. It utilizes fine-grained structure aggregation for improved accuracy and offers a compact model.
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FSA-Net is an open-source research tool designed for head pose estimation from a single image, developed by Tsun-Yi Yang. Published at CVPR19, it introduces a novel approach based on regression and fine-grained feature aggregation. Unlike previous methods that often rely on landmark or depth estimation, FSA-Net aims for a more compact model by employing a soft stagewise regression scheme. A key innovation is its ability to learn fine-grained structure mapping to spatially group features before aggregation, providing part-based information and pooled values. The tool supports various face detectors like LBP, MTCNN, and SSD for robust and fast performance. It is implemented in Keras and TensorFlow, making it accessible for researchers and developers in computer vision and facial analysis.
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