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Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"
This is a PyTorch-based computer vision library for detecting 2D and 3D facial landmark coordinates. It functions as a facial landmark detector and reconstruction tool, utilizing deep learning to identify precise geometric points on human faces from image datasets. The library allows for the selection of specific detection backends to balance accuracy and processing speed. It supports the integration of precomputed bounding box files, which enables the system to bypass the initial detection phase and proceed directly to landmark extraction. The toolkit includes capabilities for batch image p
High-level batteries-included neural network training library for Pytorch
Split-Attention Network, A New ResNet Variant. It significantly boosts the performance of downstream models such as Mask R-CNN, Cascade R-CNN and DeepLabV3.
The main features of zhanghang1989/resnest are: Attention Mechanisms, Computer Vision.
Projects with overlapping indexed features include: jongchan/attention-module — Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention… hujie-frank/senet — Squeeze-and-Excitation Networks. 1adrianb/face-alignment — This is a PyTorch-based computer vision library for detecting 2D and 3D facial landmark coordinates. It functions as a… ailab-cvc/yolo-world — YOLO-World is a vision-language framework and open-vocabulary object detection model. It identifies objects in images… airctic/icevision. achaiah/pywick — High-level batteries-included neural network training library for Pytorch.
