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iVMCL / AOGNets

Official implementation for our CVPR19 paper, AOGNets: Compositional Grammatical Architectures for Deep Learning
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model used for detection #3

Open xjtuwh opened 5 years ago

xjtuwh commented 5 years ago

Hello! I'm interested in this work. I use AOGNets to faster R-CNN as your paper intorduced. I use the code from https://github.com/jwyang/faster-rcnn.pytorch/tree/pytorch-1.0. And I make a aog.py in lib/model/faster_rcnn you do. The issue is that when I run train_val to train the model end to end, The loss is so high normally. I want to know where is the problem. Is it related to FP-optimizer? If yes, what should I do for this issues? I'm looking forward to your reply! Best wishes! 图片 图片

I use the pretrained model in your google driver.

tfwu commented 4 years ago

Please check our https://github.com/iVMCL/AttentiveNorm_Detection