Qibin Hou
Also known as Andrew Hou, Qi-Bin Hou, 侯淇彬
Qibin Hou is a computer vision researcher whose network designs for image recognition, segmentation and generation include Coordinate Attention, VOLO, SegNeXt and StoryDiffusion. He completed a Ph.D. at Nankai University in 2019 under Ming-Ming Cheng, after presenting a saliency-detection method with short connections at CVPR 2017. A research fellowship at the National University of Singapore with Jiashi Feng and Shuicheng Yan ran from 2019 to 2021. In 2021, he coauthored VOLO, the first model above 87% top-1 accuracy on ImageNet-1K without extra training data, and in 2022 he received the first prize in natural science from China's Ministry of Education. He is an associate professor at the School of Computer Science at Nankai University.
- Now at
- Nankai University and Nankai International Advanced Research Institute (Shenzhen Futian)
Timeline
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2017–2019
Saliency work and a Nankai PhD
With Ming-Ming Cheng and four other coauthors, he presents Deeply Supervised Salient Object Detection With Short Connections at CVPR 2017, adding short connections to the skip-layer structures of the HED architecture. He receives his Ph.D. from Nankai University in June 2019 under Cheng's supervision.
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August 2019–August 2021
Research fellow at NUS
From August 2019 to August 2021, he works as a research fellow at the National University of Singapore with Jiashi Feng and Shuicheng Yan.
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2020–2022
Two natural science prizes
He receives a second prize in natural science from CAAI in 2020 and a first prize in natural science from China's Ministry of Education in 2022.
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2021
Coordinate Attention and VOLO
His paper Coordinate Attention for Efficient Mobile Network Design, written with Daquan Zhou and Jiashi Feng, appears at CVPR 2021 and plugs into mobile networks such as MobileNetV2 and EfficientNet with almost no extra computation. In 2021, he also coauthors VOLO with Li Yuan, Zihang Jiang, Jiashi Feng and Shuicheng Yan; it reaches 87.1% top-1 accuracy on ImageNet-1K, the first model above 87% without extra training data.
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2022
SegNeXt and Conv2Former
In 2022, he coauthors SegNeXt, a convolutional attention network for semantic segmentation that reaches 90.6% mIoU on the Pascal VOC 2012 test leaderboard with a tenth of the parameters of EfficientNet-L2 w/ NAS-FPN. As first author of Conv2Former, he builds a family of ConvNets on a convolutional modulation operation, and they outperform Swin Transformer and ConvNeXt on ImageNet classification, COCO detection and ADE20k segmentation.
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2024
StoryDiffusion for consistent images
In 2024, he coauthors StoryDiffusion with Yupeng Zhou, Daquan Zhou, Ming-Ming Cheng and Jiashi Feng. Its Consistent Self-Attention keeps subjects consistent across images from pretrained diffusion-based text-to-image models in a zero-shot manner, and a Semantic Motion Predictor extends the images to long videos.
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As of October 2026
Associate professor at Nankai
He is an associate professor at the School of Computer Science at Nankai University in Tianjin, and he is also with the Nankai International Advanced Research Institute (Shenzhen Futian). His research builds AI models that help agents see and understand the complex world.
Career
- NowNankai UniversityAssociate Professor
- NowNankai International Advanced Research Institute (Shenzhen Futian)
- 2019–2021National University of SingaporeResearch Fellow
Education
- 2019Nankai UniversityPh.D.
Sources and credits
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- Qibin's Homepage - HVision @ Nankai
- Deeply Supervised Salient Object Detection With Short Connections (CVPR 2017 Open Access Repository)
- Awards - HVision @ Nankai
- Coordinate Attention for Efficient Mobile Network Design (CVPR 2021 Open Access Repository)
- VOLO: Vision Outlooker for Visual Recognition
- SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation
- Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognition
- StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation
- Qibin (Andrew) Hou 侯淇彬 – 程明明个人主页


