Research on Client Detection of BitTorrent Based on Content. - Yingxu Qiao; Hong-guo Yang (CSEE (2), 2011)

D-MSCD: Mean-Standard Deviation Curve Descriptor Based on Deep Learning. - Zhanqiang Huo; Guangxing Du; Fen Luo; Yingxu Qiao; Junwei Luo (IEEE Access, 2020)

Deep High-Resolution Network With Double Attention Residual Blocks for Human Pose Estimation. - Zhanqiang Huo; Han Jin; Yingxu Qiao; Fen Luo (IEEE Access, 2020)

Learning Multi-Level Features to Improve Crowd Counting. - Zhanqiang Huo; Bin Lu; Aizhong Mi; Fen Luo; Yingxu Qiao (IEEE Access, 2020)

Towards learning line descriptors from patches: a new paradigm and large-scale dataset. - Hongmin Liu 001; Yujie Liu; Miaomiao Fu; Yuhui Wei; Zhanqiang Huo; Yingxu Qiao (Int. J. Mach. Learn. Cybern., 2021)

Efficient Style-Corpus Constrained Learning for Photorealistic Style Transfer. - Yingxu Qiao; Jiabao Cui; Fuxian Huang; Hongmin Liu 001; Cuizhu Bao; Xi Li 001 (IEEE Trans. Image Process., 2021)

Detail Recovery and Color Enhancement for Single Image Dehazing. - Wangming Fang; Zhanqiang Huo; Yingxu Qiao (ICNCC, 2022)

Low-light Image Enhancement via Unsupervised Progressive Fusion Network. - Hengxuan Li; Zhanqiang Huo; Yingxu Qiao (ICNCC, 2022)

Realistic Nighttime Haze Image Generation with Glow Effect. - Yading Zheng; Aizhong Mi; Yingxu Qiao; Yijiang Wang (ICNCC, 2022)

Efficient photorealistic style transfer with multi-order image statistics. - Zhanqiang Huo; Xueli Li; Yingxu Qiao; Panbo Zhou; Jing Wang 093 (Appl. Intell., 2022)

High quality proposal feature generation for crowded pedestrian detection. - Jing Wang 093; Cailing Zhao; Zhanqiang Huo; Yingxu Qiao; Haifeng Sima (Pattern Recognit., 2022)

Boosting Object Detection in Foggy Scenes via Dark Channel Map and Union Training Strategy. - Zhanqiang Huo; Sensen Meng; Yingxu Qiao; Fen Luo (PRCV (12), 2023)

PVT-Crowd: Bridging Multi-scale Features from Pyramid Vision Transformer for Weakly-Supervised Crowd Counting. - Zhanqiang Huo; Kunwei Zhang; Fen Luo; Yingxu Qiao (PRCV (9), 2023)

Semantics recalibration and detail enhancement network for real-time semantic segmentation. - Aizhong Mi; Mingming Gao; Zhanqiang Huo; Yingxu Qiao; Jian Chen; Haiyang Jia (IET Comput. Vis., 2023)

Domain adaptive crowd counting via dynamic scale aggregation network. - Zhanqiang Huo; Yanan Wang; Yingxu Qiao; Jing Wang 093; Fen Luo (IET Comput. Vis., 2023)

Dual-route synthetic-to-real adaption for single image dehazing. - Yingxu Qiao; Zhanqiang Huo; Sensen Meng (IET Image Process., 2024)

Rethinking Zero-DCE for Low-Light Image Enhancement. - Aizhong Mi; Wenhui Luo; Yingxu Qiao; Zhanqiang Huo (Neural Process. Lett., 2024)

Robust Synthetic-to-Real Ensemble Dehazing Algorithm With the Intermediate Domain. - Yingxu Qiao; Xing Wang; Hongmin Liu 001; Zhanqiang Huo (IEEE Trans. Comput. Soc. Syst., 2024)

More Realistic Edges, Textures, and Colors for Image Non-Homogeneous Dehazing. - Hairu Guo; Yaning Li; Zhanqiang Huo; Shan Zhao; Yingxu Qiao (IET Image Process., 2025)

Dark channel map and union training strategy for object detection in foggy scenes. - Zhanqiang Huo; Sen Li; Sensen Meng; Yingxu Qiao; Shan Zhao; Luyao Liu (Pattern Recognit. Lett., 2025)

Combining implicit and explicit priors for zero-reference low-light image enhancement and denoising. - Jinxia Yu; Fabao Xue; Zhanqiang Huo; Yingxu Qiao (Multim. Syst., 2025)

D3-Dehaze: a divide-and-conquer framework for enhanced single image dehazing. - Zhanqiang Huo; Xiyan Zhan; Yingxu Qiao; Shan Zhao (Vis. Comput., 2025)