118 citations · 360 across the 17 of their papers we have counts for
8 papers · 1 filter
Joint Adversarial Training: Incorporating both Spatial and Pixel Attacks
Haichao Zhang, Jianyu Wang
Conventional adversarial training methods using attacks that manipulate the pixel value directly and individually, leading to models that are less robust in face of spatial transfo…
Towards Adversarially Robust Object Detection
Haichao Zhang, Jianyu Wang
Object detection is an important vision task and has emerged as an indispensable component in many vision system, rendering its robustness as an increasingly important performance…
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training
Haichao Zhang, Jianyu Wang
We introduce a feature scattering-based adversarial training approach for improving model robustness against adversarial attacks. Conventional adversarial training approaches lever…
Bilateral Adversarial Training: Towards Fast Training of More Robust Models Against Adversarial Attacks
Jianyu Wang, Haichao Zhang
In this paper, we study fast training of adversarially robust models. From the analyses of the state-of-the-art defense method, i.e., the multi-step adversarial training, we hypoth…
Enhance Visual Recognition under Adverse Conditions via Deep Networks
Ding Liu, Bowen Cheng, Zhangyang Wang +2
Visual recognition under adverse conditions is a very important and challenging problem of high practical value, due to the ubiquitous existence of quality distortions during image…
Non-Uniform Blind Deblurring with a Spatially-Adaptive Sparse Prior
Haichao Zhang, David Wipf
Typical blur from camera shake often deviates from the standard uniform convolutional script, in part because of problematic rotations which create greater blurring away from some…
Revisiting Bayesian Blind Deconvolution
David Wipf, Haichao Zhang
Blind deconvolution involves the estimation of a sharp signal or image given only a blurry observation. Because this problem is fundamentally ill-posed, strong priors on both the s…
Image Super-Resolution via Sparse Bayesian Modeling of Natural Images
Haichao Zhang, David Wipf, Yanning Zhang
Image super-resolution (SR) is one of the long-standing and active topics in image processing community. A large body of works for image super resolution formulate the problem with…