46 citations · 67 across the 3 of their papers we have counts for
6 papers
Human Attention-Guided Explainable Artificial Intelligence for Computer Vision Models
Guoyang Liu, Jindi Zhang, Antoni B. Chan +1
We examined whether embedding human attention knowledge into saliency-based explainable AI (XAI) methods for computer vision models could enhance their plausibility and faithfulnes…
ODAM: Gradient-based instance-specific visual explanations for object detection
Chenyang Zhao, Antoni B. Chan
We propose the gradient-weighted Object Detector Activation Maps (ODAM), a visualized explanation technique for interpreting the predictions of object detectors. Utilizing the grad…
TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization
Ziquan Liu, Yi Xu, Xiangyang Ji +1
Recent years have seen the ever-increasing importance of pre-trained models and their downstream training in deep learning research and applications. At the same time, the defense…
Pareto Optimization for Active Learning under Out-of-Distribution Data Scenarios
Xueying Zhan, Zeyu Dai, Qingzhong Wang +4
Pool-based Active Learning (AL) has achieved great success in minimizing labeling cost by sequentially selecting informative unlabeled samples from a large unlabeled data pool and…
Crowd Counting by Adapting Convolutional Neural Networks with Side Information
Di Kang, Debarun Dhar, Antoni B. Chan
Computer vision tasks often have side information available that is helpful to solve the task. For example, for crowd counting, the camera perspective (e.g., camera angle and heigh…
Heterogeneous Multi-task Learning for Human Pose Estimation with Deep Convolutional Neural Network
Sijin Li, Zhi-Qiang Liu, Antoni B. Chan
We propose an heterogeneous multi-task learning framework for human pose estimation from monocular image with deep convolutional neural network. In particular, we simultaneously le…