activity
20192022
most citedTowards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack

58 citations · 74 across the 10 of their papers we have counts for

collaborators

11 papers

cs.CV20222 cited

CREAM: Weakly Supervised Object Localization via Class RE-Activation Mapping

Jilan Xu, Junlin Hou, Yuejie Zhang +5

Weakly Supervised Object Localization (WSOL) aims to localize objects with image-level supervision. Existing works mainly rely on Class Activation Mapping (CAM) derived from a clas…

cs.CV2022

Scale-Invariant Adversarial Attack for Evaluating and Enhancing Adversarial Defenses

Mengting Xu, Tao Zhang, Zhongnian Li +1

Efficient and effective attacks are crucial for reliable evaluation of defenses, and also for developing robust models. Projected Gradient Descent (PGD) attack has been demonstrate…

cs.CV2021

M3D-VTON: A Monocular-to-3D Virtual Try-On Network

Fuwei Zhao, Zhenyu Xie, Michael Kampffmeyer +5

Virtual 3D try-on can provide an intuitive and realistic view for online shopping and has a huge potential commercial value. However, existing 3D virtual try-on methods mainly rely…

cs.CV202158 cited

Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack

Mengting Xu, Tao Zhang, Zhongnian Li +2

Deep learning models (with neural networks) have been widely used in challenging tasks such as computer-aided disease diagnosis based on medical images. Recent studies have shown d…

cs.RO20201 cited

Generative Partial Visual-Tactile Fused Object Clustering

Tao Zhang, Yang Cong, Gan Sun +3

Visual-tactile fused sensing for object clustering has achieved significant progresses recently, since the involvement of tactile modality can effectively improve clustering perfor…

cs.CV20202 cited

Re-weighting and 1-Point RANSAC-Based PnP Solution to Handle Outliers

Haoyin Zhou, Tao Zhang, Jagadeesan Jayender

The ability to handle outliers is essential for performing the perspective-n-point (PnP) approach in practical applications, but conventional RANSAC+P3P or P4P methods have high ti…