182 citations · 461 across the 8 of their papers we have counts for
5 papers · 1 filter
Exploring the Vulnerability of Single Shot Module in Object Detectors via Imperceptible Background Patches
Yuezun Li, Xiao Bian, Ming-ching Chang +1
Recent works succeeded to generate adversarial perturbations on the entire image or the object of interests to corrupt CNN based object detectors. In this paper, we focus on explor…
Robust Adversarial Perturbation on Deep Proposal-based Models
Yuezun Li, Daniel Tian, Ming-Ching Chang +2
Adversarial noises are useful tools to probe the weakness of deep learning based computer vision algorithms. In this paper, we describe a robust adversarial perturbation (R-AP) met…
Who did What at Where and When: Simultaneous Multi-Person Tracking and Activity Recognition
Wenbo Li, Ming-Ching Chang, Siwei Lyu
We present a bootstrapping framework to simultaneously improve multi-person tracking and activity recognition at individual, interaction and social group activity levels. The infer…
In Ictu Oculi: Exposing AI Generated Fake Face Videos by Detecting Eye Blinking
Yuezun Li, Ming-Ching Chang, Siwei Lyu
The new developments in deep generative networks have significantly improve the quality and efficiency in generating realistically-looking fake face videos. In this work, we descri…
Multi-Scale Structure-Aware Network for Human Pose Estimation
Lipeng Ke, Ming-Ching Chang, Honggang Qi +1
We develop a robust multi-scale structure-aware neural network for human pose estimation. This method improves the recent deep conv-deconv hourglass models with four key improvemen…