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JDAI-CV / FADA

(ECCV 2020) Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation

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About Cross-City?

BinhuiXie opened this issue · comments

commented

Hi! Great work!
I have a quick question: when I conduct adaptation between real images from different cities, i.e., Cityscapes to Cross-City, but becaues the Cross-City only defines 13 major classes for annotations, should I set NUM_CLASSES=13 and adjust the id_to_trained in dataset or leave it unchanged and then report the results of the shared 13 classes?

Thanks in advance
binhui

commented

Hi, I trained the model with NUM_CLASSES=19 when performing Cityscapes to Cross-City and reported the results of Cross-City's 13 classes.