84 citations · 115 across the 24 of their papers we have counts for
7 papers · 1 filter
Personalized Face Privacy Protection From a Single Image
Zachary Yahn, Fatih Ilhan, Tiansheng Huang +5
Photos of faces uploaded online are vulnerable to malicious actors who can scrape facial images from online sources and intrude on personal privacy via unauthorized use of facial r…
A Multi-Agent Perception-Action Alliance for Efficient Long Video Reasoning
Yichang Xu, Gaowen Liu, Ramana Rao Kompella +6
This paper presents a multi-agent perception-action exploration alliance, dubbed A4VL, for efficient long-video reasoning. A4VL operates in a multi-round perception-action explorat…
Adversarial Attention Perturbations for Large Object Detection Transformers
Zachary Yahn, Selim Furkan Tekin, Fatih Ilhan +5
Adversarial perturbations are useful tools for exposing vulnerabilities in neural networks. Existing adversarial perturbation methods for object detection are either limited to att…
A Neurosymbolic Agent System for Compositional Visual Reasoning
Yichang Xu, Gaowen Liu, Ramana Rao Kompella +5
The advancement in large language models (LLMs) and large vision models has fueled the rapid progress in multi-modal vision-language reasoning capabilities. However, existing visio…
Joint-Motion Mutual Learning for Pose Estimation in Videos
Sifan Wu, Haipeng Chen, Yifang Yin +5
Human pose estimation in videos has long been a compelling yet challenging task within the realm of computer vision. Nevertheless, this task remains difficult because of the comple…
Personalized Privacy Protection Mask Against Unauthorized Facial Recognition
Ka-Ho Chow, Sihao Hu, Tiansheng Huang +1
Face recognition (FR) can be abused for privacy intrusion. Governments, private companies, or even individual attackers can collect facial images by web scraping to build an FR sys…
Robust Few-Shot Ensemble Learning with Focal Diversity-Based Pruning
Selim Furkan Tekin, Fatih Ilhan, Tiansheng Huang +4
This paper presents FusionShot, a focal diversity optimized few-shot ensemble learning approach for boosting the robustness and generalization performance of pre-trained few-shot m…