wofmanaf/SA-Net
quality grade F, 19 out of 100Code for our ICASSP 2021 paper: SA-Net: Shuffle Attention for Deep Convolutional Neural Networks
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Detection, segmentation, tracking, OCR models, 3D reconstruction and classical vision.
Signals: computer-vision, object-detection, image-segmentation, yolo, opencv, image-classification, pose-estimation, object-tracking
1,478 results
Code for our ICASSP 2021 paper: SA-Net: Shuffle Attention for Deep Convolutional Neural Networks
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Face recognition and analytics library based on deep neural networks and ONNX runtime
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