awesome-semantic-segmentation

Lists implementations of major architectures like U-Net, DeepLab, and Mask R-CNN across PyTorch, TensorFlow, Keras, and Caffe, as shown in the detailed 'Networks by architecture' sections.

Resources are categorized by framework (e.g., PyTorch, Keras), making it easy for users committed to a specific ecosystem to find relevant code, evidenced by separate links for each framework under models.

Includes specialized sections for medical imaging, satellite imagery, autonomous driving, and video segmentation, providing targeted resources for niche domains beyond general computer vision.

Curates links to popular benchmarks like mmsegmentation and datasets such as Cityscapes and COCO, aiding in model evaluation and training, as listed under 'Benchmarks' and 'Datasets'.