ImageNet-E: Benchmarking Neural Network Robustness via Attribute Editing

30 March 2023

Papers citing "ImageNet-E: Benchmarking Neural Network Robustness via Attribute Editing"

8 / 8 papers shown

Title
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 305 7,434 0 11 Nov 2021
Are Transformers More Robust Than CNNs? Yutong Bai Jieru Mei Alan Yuille Cihang Xie ViT AAML 192 258 0 10 Nov 2021
ResNet strikes back: An improved training procedure in timm Ross Wightman Hugo Touvron Hervé Jégou AI4TS 209 487 0 01 Oct 2021
On the Importance of Gradients for Detecting Distributional Shifts in the Wild Rui Huang Andrew Geng Yixuan Li 189 328 0 01 Oct 2021
Recent Advances in Adversarial Training for Adversarial Robustness Tao Bai Jinqi Luo Jun Zhao B. Wen Qian Wang AAML 73 473 0 02 Feb 2021
A Survey on Deep Learning in Medical Image Analysis G. Litjens Thijs Kooi B. Bejnordi A. Setio F. Ciompi Mohsen Ghafoorian Jeroen van der Laak Bram van Ginneken C. I. Sánchez OOD 283 10,613 0 19 Feb 2017
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 252 36,362 0 25 Aug 2016
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 296 39,194 0 01 Sep 2014