Papers
Defending Against Universal Perturbations With Shared Adversarial Training
Chaithanya Kumar Mummadi, Thomas Brox, Jan Hendrik Metzen
Rethinking ImageNet Pre-Training
Kaiming He, Ross Girshick, Piotr Dollar
Bayesian Optimized 1-Bit CNNs
Jiaxin Gu, Junhe Zhao, Xiaolong Jiang et al.
Universal Perturbation Attack Against Image Retrieval
Jie Li, Rongrong Ji, Hong Liu et al.
A Geometry-Inspired Decision-Based Attack
Yujia Liu, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard
Improving Adversarial Robustness via Guided Complement Entropy
Hao-Yun Chen, Jhao-Hong Liang, Shih-Chieh Chang et al.
Proximal Mean-Field for Neural Network Quantization
Thalaiyasingam Ajanthan, Puneet K. Dokania, Richard Hartley et al.
The LogBarrier Adversarial Attack: Making Effective Use of Decision Boundary Information
Chris Finlay, Aram-Alexandre Pooladian, Adam Oberman
Differentiable Soft Quantization: Bridging Full-Precision and Low-Bit Neural Networks
Ruihao Gong, Xianglong Liu, Shenghu Jiang et al.
Scalable Verified Training for Provably Robust Image Classification
Sven Gowal, Krishnamurthy (Dj) Dvijotham, Robert Stanforth et al.
Wasserstein GAN With Quadratic Transport Cost
Huidong Liu, Xianfeng Gu, Dimitris Samaras
Physical Adversarial Textures That Fool Visual Object Tracking
Rey Reza Wiyatno, Anqi Xu
Better and Faster: Exponential Loss for Image Patch Matching
Shuang Wang, Yanfeng Li, Xuefeng Liang et al.
Sym-Parameterized Dynamic Inference for Mixed-Domain Image Translation
Simyung Chang, SeongUk Park, John Yang et al.
On the Efficacy of Knowledge Distillation
Jang Hyun Cho, Bharath Hariharan
Hilbert-Based Generative Defense for Adversarial Examples
Yang Bai, Yan Feng, Yisen Wang et al.
Semantic Adversarial Attacks: Parametric Transformations That Fool Deep Classifiers
Ameya Joshi, Amitangshu Mukherjee, Soumik Sarkar et al.
Small Steps and Giant Leaps: Minimal Newton Solvers for Deep Learning
Joao F. Henriques, Sebastien Ehrhardt, Samuel Albanie et al.
A Tour of Convolutional Networks Guided by Linear Interpreters
Pablo Navarrete Michelini, Hanwen Liu, Yunhua Lu et al.
Implicit Surface Representations As Layers in Neural Networks
Mateusz Michalkiewicz, Jhony K. Pontes, Dominic Jack et al.
Enhancing Adversarial Example Transferability With an Intermediate Level Attack
Qian Huang, Isay Katsman, Horace He et al.
Sparse and Imperceivable Adversarial Attacks
Francesco Croce, Matthias Hein
What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis
Jeonghun Baek, Geewook Kim, Junyeop Lee et al.
Towards Unconstrained End-to-End Text Spotting
Siyang Qin, Alessandro Bissacco, Michalis Raptis et al.
Zero-Shot Grounding of Objects From Natural Language Queries
Arka Sadhu, Kan Chen, Ram Nevatia