This is the unofficial code of Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes. which achieve state-of-the-art trade-off between accuracy and speed on cityscapes and camvid, without using inference acceleration and extra data
Semantic Scene Completion
Easy to use pytorch-implementation of DDRNet on Cityscapes dataset
Tensorflow-Keras semantic segmentation
🚦 Train and evaluate semantic segmentation models on the Cityscapes dataset using PyTorch with DeepLabV3/DeepLabV3+ for precise pixel-wise predictions.
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