项目作者: rgeirhos

项目描述 :
Pre-trained models, data, code & materials from the paper "ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness" (ICLR 2019 Oral)
高级语言: R
项目地址: git://github.com/rgeirhos/texture-vs-shape.git
创建时间: 2018-11-28T09:56:15Z
项目社区:https://github.com/rgeirhos/texture-vs-shape

开源协议:

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trained_conflict_content_1647656723353.pdf
trained_conflict_texture-crop_1647656723393.pdf
trained_conflict_texture_1647656723445.pdf
barplots_all_0-crop_1647656720741.pdf
barplots_all_0_1647656720894.pdf
barplots_all_90-crop_1647656721008.pdf
barplots_all_90_1647656721093.pdf
trained_barplots_all_0-crop_1647656721157.pdf
trained_barplots_all_0_1647656721221.pdf
trained_barplots_all_90-crop_1647656721270.pdf
trained_barplots_all_90_1647656721349.pdf
conflict_content-crop_1647656721405.pdf
conflict_content_1647656721446.pdf
conflict_texture-crop_1647656721473.pdf
conflict_texture_1647656721482.pdf
alexnet_trained_conflict_content-crop_1647656721499.pdf
alexnet_trained_conflict_content_1647656721672.pdf
alexnet_vgg_trained_conflict_content-crop_1647656721708.pdf
alexnet_vgg_trained_conflict_content_1647656721812.pdf
conflict_content-crop_1647656721876.pdf
conflict_content_1647656721917.pdf
conflict_texture-crop_1647656721974.pdf
conflict_texture_1647656722025.pdf
densenet121_trained_conflict_content-crop_1647656722034.pdf
densenet121_trained_conflict_content_1647656722048.pdf
densenet_conflict_content-crop_1647656722118.pdf
densenet_conflict_content_1647656722197.pdf
other_networks_conflict_content-crop_1647656722218.pdf
other_networks_conflict_content_1647656722322.pdf
resnet101_oidv2_conflict_content-crop_1647656722358.pdf
resnet101_oidv2_conflict_content_1647656722541.pdf
squeezenet1_1_trained_conflict_content-crop_1647656722596.pdf
squeezenet1_1_trained_conflict_content_1647656722658.pdf
trained_conflict_content-crop_1647656722722.pdf
trained_conflict_content_1647656722800.pdf
trained_conflict_texture-crop_1647656722847.pdf
trained_conflict_texture_1647656722876.pdf
vgg16_trained_conflict_content-crop_1647656722941.pdf
vgg16_trained_conflict_content_1647656722992.pdf
conflict_content-crop_1647656723048.pdf
conflict_content_1647656723097.pdf
conflict_texture-crop_1647656723106.pdf
conflict_texture_1647656723130.pdf
conflict_content-crop_1647656723166.pdf
conflict_content_1647656723213.pdf
conflict_texture-crop_1647656723248.pdf
conflict_texture_1647656723276.pdf
trained_conflict_content-crop_1647656723301.pdf