Ye, Qixiang

YOLOv12: Attention-Centric Real-Time Object Detectors

Tian, Y., Ye, Q., & Doermann, D. (2025) · arXiv

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 882

Orientation robust object detection in aerial images using deep convolutional neural network

Zhu, H., Chen, X., Dai, W., Fu, K., Ye, Q., & Jiao, J. (2015) · 2015 IEEE International Conference on Image Processing (ICIP)

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 483

Soft Proposal Networks for Weakly Supervised Object Localization

Zhu, Y., Zhou, Y., Ye, Q., Qiu, Q., & Jiao, J. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 156

Multiple Instance Active Learning for Object Detection

Yuan, T., Wan, F., Fu, M., Liu, J., Xu, S., Ji, X., & Ye, Q. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Machine Learning and AlgorithmsAdvanced Neural Network Applications

Cited by 155

Domain General Face Forgery Detection by Learning to Weight

Sun, K., Liu, H., Ye, Q., Gao, Y., Liu, J., Shao, L., & Ji, R. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence

Digital Media Forensic DetectionFace recognition and analysis

Cited by 155

Ray denoising: Depth-aware hard negative sampling for multi-view 3d object detection

Liu, F., Huang, T., Zhang, Q., Yao, H., Zhang, C., Wan, F., Ye, Q., & Zhou, Y. (2025) · Lecture Notes in Computer Science

Advanced Neural Network Applications3D Shape Modeling and Analysis

Cited by 33