JTGD trains a CycleGAN to synthesize road defects and jointly hardens an InternImage-T detector, reporting 63.13 average F1 on RDD2022 with 49M parameters versus 59.20 F1 and 253M parameters for Faster Swin.
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Joint Training of Image Generator and Detector for Road Defect Detection
JTGD trains a CycleGAN to synthesize road defects and jointly hardens an InternImage-T detector, reporting 63.13 average F1 on RDD2022 with 49M parameters versus 59.20 F1 and 253M parameters for Faster Swin.