Qibin (Andrew) Hou 侯淇彬

Qibin Hou (houqb AT nankai DOT edu DOT cn) is currently an associate professor at School of Computer Science, Nankai University. He received his Ph.D. degree in 2019 and then spent two years working with Prof. Jiashi Feng and Prof. Shuicheng Yan as a research fellow at NUS. His research interests include deep learning and computer vision.

You can also reach me via andrewhoux AT gmail DOT com.

侯淇彬，副教授，南开大学“百青计划”入选者，博士生导师，天津市优博。主要研究方向为计算机视觉与深度学习，主持国家自然科学基金委面上项目，目前已在IEEE TPAMI / NeurIPS / CVPR / ICCV等国际顶级期刊及会议上发表论文40余篇，Google Scholar引用10000余次，两篇一作论文引用1600+，单篇一作论文最高引用2100余次，根据Best Paper Digest网站统计该论文影响力在所有1660篇CVPR 2021录用论文中排名第四位 ，发表于IEEE TPAMI的VOLO工作实现了 ImageNet 分类准确度首个87%+的新突破。研究成果应用于华为旗舰手机智能拍照系统中并获得了华为公司2017年度优秀合作成果奖，入选第七届中国科协青年人才托举计划，曾获世界互联网大会领先科技奖（246进15）并获中央二套直播报道、教育部自然科学奖一等奖、吴文俊人工智能科学技术奖自然科学二等奖等奖项。

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Selected Publications (Please refer to my [Google Scholar] or [Semantic Scholar] for more publications.)

Journal Papers

• Zhaohui Zheng, Rongguang Ye, Qibin Hou*, Dongwei Ren, Ping Wang, Wangmeng Zuo, and Ming-Ming Cheng. “Localization distillation for object detection.” IEEE Transactions on Pattern Analysis and Machine Intelligence (2023).
• Qibin Hou*, Zihang Jiang, Li Yuan, Ming-Ming Cheng, Shuicheng Yan, and Jiashi Feng. “Vision Permutator: A Permutable MLP-Like Architecture for Visual Recognition.” IEEE Transactions on Pattern Analysis & Machine Intelligence 45, no. 01 (2023): 1328-1334.
• Li Yuan#, Qibin Hou#, Zihang Jiang#, Jiashi Feng, and Shuicheng Yan*. “VOLO: Vision Outlooker for Visual Recognition.” IEEE Transactions on Pattern Analysis & Machine Intelligence 45, no. 05 (2023): 6575-6586.
• Daquan Zhou, Qibin Hou, Linjie Yang, Xiaojie Jin, and Jiashi Feng. “Token Selection is a Simple Booster for Vision Transformers.” IEEE Transactions on Pattern Analysis and Machine Intelligence (2022).
• Jiang-Jiang Liu, Qibin Hou, Zhi-Ang Liu, and Ming-Ming Cheng. “Poolnet+: Exploring the potential of pooling for salient object detection.” IEEE Transactions on Pattern Analysis and Machine Intelligence 45, no. 1 (2022): 887-904.
• Peng-Tao Jiang, Ling-Hao Han, Qibin Hou, Ming-Ming Cheng, and Yunchao Wei. “Online attention accumulation for weakly supervised semantic segmentation.” IEEE Transactions on Pattern Analysis and Machine Intelligence 44, no. 10 (2021): 7062-7077.
• Qibin Hou, Ming-Ming Cheng, Xiaowei Hu, Ali Borji, Zhuowen Tu, and Philip HS Torr. “Deeply Supervised Salient Object Detection with Short Connections.” IEEE Transactions on Pattern Analysis and Machine Intelligence 41, no. 4 (2019): 815-828.

Conference Papers

• Yupeng Zhou, Zhen Li, Chun-Le Guo, Song Bai, Ming-Ming Cheng, and Qibin Hou*. “SRFormer: Permuted Self-Attention for Single Image Super-Resolution.” In ICCV, 2023.
• Yuxuan Li, Qibin Hou, Zhaohui Zheng, Ming-Ming Cheng, Jian Yang, and Xiang Li. “Large Selective Kernel Network for Remote Sensing Object Detection.” In ICCV, 2023.
• Zhen Li, Zuo-Liang Zhu, Ling-Hao Han, Qibin Hou, Chun-Le Guo, and Ming-Ming Cheng. “AMT: All-Pairs Multi-Field Transforms for Efficient Frame Interpolation.” In CVPR, pp. 9801-9810. 2023.
• Peng-Tao Jiang, Yuqi Yang, Qibin Hou*, and Yunchao Wei. “L2g: A simple local-to-global knowledge transfer framework for weakly supervised semantic segmentation.” In CVPR, pp. 16886-16896. 2022.
• Zhaohui Zheng#, Rongguang Ye#, Ping Wang, Dongwei Ren, Wangmeng Zuo, Qibin Hou*, and Ming-Ming Cheng. “Localization distillation for dense object detection.” In CVPR, pp. 9407-9416. 2022.
• Meng-Hao Guo, Cheng-Ze Lu, Qibin Hou, Zhengning Liu, Ming-Ming Cheng, and Shi-Min Hu. “Segnext: Rethinking convolutional attention design for semantic segmentation.” NeurIPS 35 (2022): 1140-1156.
• Zi-Hang Jiang, Qibin Hou*, Li Yuan, Daquan Zhou, Yujun Shi, Xiaojie Jin, Anran Wang, and Jiashi Feng. “All tokens matter: Token labeling for training better vision transformers.” NeurIPS 34 (2021): 18590-18602.
• Hou, Qibin, Daquan Zhou, and Jiashi Feng. “Coordinate attention for efficient mobile network design.” In CVPR. 2021.
• Hou, Qibin, Li Zhang, Ming-Ming Cheng, and Jiashi Feng. “Strip pooling: Rethinking spatial pooling for scene parsing.” In CVPR, pp. 4003-4012. 2020.
• Jiang-Jiang Liu#, Qibin Hou#, Ming-Ming Cheng, Changhu Wang, and Jiashi Feng. “Improving convolutional networks with self-calibrated convolutions.” In CVPR, pp. 10096-10105. 2020.
• Daquan Zhou#, Qibin Hou#, Yunpeng Chen, Jiashi Feng, and Shuicheng Yan. “Rethinking bottleneck structure for efficient mobile network design.” In ECCV, pp. 680-697. Springer International Publishing, 2020.
• Jiang-Jiang Liu#, Qibin Hou#, Ming-Ming Cheng*, Jiashi Feng, and Jianmin Jiang. “A simple pooling-based design for real-time salient object detection.” In CVPR, pp. 3917-3926. 2019.
• Qibin Hou, PengTao Jiang, Yunchao Wei, and Ming-Ming Cheng*. “Self-erasing network for integral object attention.” NeurIPS 31 (2018).

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Teaching

2022-2023 Spring    Deep learning

2023-2024 Spring    Deep learning

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Students

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Applications

Our reduced version of DSS (CVPR2017, PAMI2019) has been used in flagship products such as Huawei Mate 10, Huawei Honour V10, etc, to create “AI Selfie: Brilliant Bokeh, perfect portraits”  effects as demonstrated in Mate 10 launch show, in Munich, Germany.