# https://github.com/pytorch/examples/blob/master/imagenet/main.py """ ifepoch<6: lr=1e-6+(args.lr-1e-6)*iteration/(epoch_size*5) else: lr=args.lr*(gamma**(step_index)) forparam_groupinoptimizer.param_groups: param_group['lr']=lr ...
This branch is1 commit behindGOATmessi7/RFBNet:master. README MIT license By Songtao Liu, Di Huang, Yunhong Wang Updates: we propose a new method to get 42.4 mAP at 45 FPS on COCO, code is availablehere Introduction Inspired by the structure of Receptive Fields (RFs) in human visual sys...
Receptive Field Block Net for Accurate and Fast Object Detection By Songtao Liu, Di Huang, Yunhong Wang Introduction Inspired by the structure of Receptive Fields (RFs) in human visual systems, we propose a novel RF Block (RFB) module, which takes the relationship between the size and eccentric...
Inspired by the structure of Receptive Fields (RFs) in human visual systems, we propose a novel RF Block (RFB) module, which takes the relationship between the size and eccentricity of RFs into account, to enhance the discriminability and robustness of features. We further assemble the RFB ...
Receptive Field Block Net for Accurate and Fast Object Detection, ECCV 2018 - GitHub - shenqi966/RFBNet: Receptive Field Block Net for Accurate and Fast Object Detection, ECCV 2018
, stronger YOLO with ONNX, TensorRT, ncnn, and OpenVino supported!!Updates: we propose a new method to get 42.4 mAP at 45 FPS on COCO, code is available hereIntroductionInspired by the structure of Receptive Fields (RFs) in human visual systems, we propose a novel RF Block (RFB) ...
MobileNet pre-trained basenet is ported fromMobileNet-Caffe, which achieves slightly better accuracy rates than the original one reported in thepaper, weight file is available at:https://drive.google.com/open?id=13aZSApybBDjzfGIdqN1INBlPsddxCK14orBaiduYun Driver. ...
2branches0tags Go to file Code Clone HTTPSGitHub CLI Open with GitHub Desktop Download ZIP Go back Go back Go back Go back This branch is even with ruinmessi:master. Pull requestCompare Latest commit Git stats 35commits README.md By Songtao Liu, Di Huang, Yunhong Wang ...
代码链接:https://github.com/ruinmessi/RFBNet 目前state-of-art的目标检测网络主要是两条路子: two-stage:先只区分前景、背景的region proposals,同时进行第一次bounding boxes位置修正,基于proposals的CNN特征,进行类别预测和第二次位置回归;可以看出来,提取proposals特征的CNN主干网络占据着重要角色,我们希望提取到的...
https://github.com/ruinmessi/RFBNet 解压后在RFBNet的data文件夹下新建VOCdevkit文件夹,将VOC数据集放进去。 修改类别。 在voc0712.py中的VOC_CLASSES中的类别修改为自己数据集的类别。修改后: VOC_CLASSES=('__background__',# always index 0