58 citations · 244 across the 16 of their papers we have counts for
3 papers · 1 filter
Variation of Gender Biases in Visual Recognition Models Before and After Finetuning
Jaspreet Ranjit, Tianlu Wang, Baishakhi Ray +1
We introduce a framework to measure how biases change before and after fine-tuning a large scale visual recognition model for a downstream task. Deep learning models trained on inc…
Multitask Learning Strengthens Adversarial Robustness
Chengzhi Mao, Amogh Gupta, Vikram Nitin +4
Although deep networks achieve strong accuracy on a range of computer vision benchmarks, they remain vulnerable to adversarial attacks, where imperceptible input perturbations fool…
AdvSPADE: Realistic Unrestricted Attacks for Semantic Segmentation
Guangyu Shen, Chengzhi Mao, Junfeng Yang +1
Due to the inherent robustness of segmentation models, traditional norm-bounded attack methods show limited effect on such type of models. In this paper, we focus on generating unr…