Yonggang Qi (齐勇刚)


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Associate Professor

Beijing University of Posts and Telecommunications, Beijing, China
Email

qiyg AT bupt DOT edu DOT cn

Google Scholar

I am currently an associate professor at BUPT. Previously, I was a PhD student at Pattern Recognition and Intelligent Systems (PRIS) laboratory at BUPT. I received the PhD in Signal Processing from Beijing University of Posts and Telecommunications (BUPT) in 2015 (Supervisor: Professor Jun Guo). From 2019 to 2020, I was a visiting scholar at SketchX lab headed by Dr. Yi-Zhe Song at the Centre for Vision Speech and Signal Processing (CVSSP) in University of Surrey. I also worked as a guest PhD at Aalborg University in Denmark in 2013 and a visiting researcher at Sun Yat-sen University in China in 2014.

My research focuses on computer vision and multimodal learning, with particular interests in human sketch related tasks, image/video generation, and diffusion models. My recent work emphasizes multimodal representation learning, cross-modal alignment, and generative modeling for complex, real-world scenarios.

招收2025年入学博士研究生一名(申请-考核、硕博连读、公开报考),欢迎带简历邮件联系。

常年招收2-4名硕士研究生(保研+考研)、科研实习生若干名(3-6个月及以上),欢迎有科研热情的同学带简历邮件联系。2025年秋季入学(专硕02方向)还有一个名额。


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Selected Publications

*: equal contribution
#: corresponding author

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Autoregressive Video Generation without Vector Quantization
Haoge Deng, Ting Pan, Haiwen Diao, Zhengxiong Luo, Yufeng Cui, Huchuan Lu, Shiguang Shan, Yonggang Qi#, Xinlong Wang#
International Conference on Learning Representations (ICLR 2025).
[ Arxiv ]--[ Github Code ]

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VersaGen: Unleashing Versatile Visual Control for Text-to-Image Synthesis
Zhipeng Chen, Lan Yang, Yonggang Qi, Honggang Zhang, Kaiyue Pang, Ke Li, & Yi-Zhe Song.
AAAI Conference on Artificial Intelligence (AAAI 2025). Oral
[ Arxiv ]--[ Github Code ]

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SAUGE: Taming SAM for Uncertainty-Aligned Multi-Granularity Edge Detection
Xing Liufu, Chaolei Tan, Xiaotong Lin, Yonggang Qi, Jinxuan Li & Jian-Fang Hu
AAAI Conference on Artificial Intelligence (AAAI 2025).
[ Arxiv ]--[ Github Code ]

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Scale-Adaptive Diffusion Model for Complex Sketch Synthesis
Jijin Hu, Ke Li, Yonggang Qi & Yi-Zhe Song.
International Conference on Learning Representations (ICLR 2024).
[ Arxiv ]--[ Github Code ]

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Zero-Shot Everything Sketch-Based Image Retrieval, and in Explainable Style
Fengyin Lin*, Mingkang Li*, Da Li, Timothy Hospedales, Yi-Zhe Song, Yonggang Qi
Computer Vision and Pattern Recognition (CVPR 2023). Highlight
[ Arxiv ]--[ Github Code ]

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SketchKnitter: Vectorized Sketch Generation with Diffusion Models
Qiang Wang, Haoge Deng, Yonggang Qi#, Da Li, Yi-Zhe Song
International Conference on Learning Representations (ICLR 2023). Spotlight
[ Paper ]--[ Github Code ]

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A Diffusion-ReFinement Model for Sketch-to-Point Modeling
Di Kong, Qiang Wang, Yonggang Qi#.
The 16th Asian Conference on Computer Vision (ACCV 2022). Oral
[ Paper ]--[ Suppl. ]--[ Github Code ]

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DiffSketching: Sketch Control Image Synthesis with Diffusion Models
Qiang Wang, Di Kong, Yonggang Qi#.
The 33rd British Machine Vision Conference (BMVC 2022).
[ Paper ]--[ Suppl. ]--[ Github Code ]

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Generative Sketch Healing
Yonggang Qi, Guoyao Su, Qiang Wang, Jie Yang, Kaiyue Pang and Yi-Zhe Song.
International Journal of Computer Vision (IJCV), Springer.
[ Paper ]--[ Project Page ]

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SketchLattice: Latticed Representation for Sketch Manipulation
Yonggang Qi*, Guoyao Su*, Pinaki Nath Chowdhury, Mingkang Li and Yi-Zhe Song.
IEEE International Conference on Computer Vision (ICCV), 2021.
[ arXiv Paper ]--[ Project Page ]--[ Github Code ]

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PQA: Perceptual Question Answering
Yonggang Qi*, Kai Zhang*, Aneeshan Sain and Yi-Zhe Song.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
[ arXiv Paper ]--[ Project Page ]--[ Github Code ]

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Towards Fine-Grained Sketch-Based 3D Shape Retrieval
Anran Qi, Yulia Gryaditskaya, Jifei Song, Yongxin Yang, Yonggang Qi, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song.
IEEE Transactions on Image Processing (TIP), 2021.
[Paper]--[ Project Page ]--[Code ]

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Towards Practical Sketch-based 3D Shape Generation: The Role of Professional Sketches
Yue Zhong, Yonggang Qi, Yulia Gryaditskaya, Honggang Zhang, and Yi-Zhe Song.
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
[ Paper ]

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SketchHealer: A Graph-to-Sequence Network for Recreating Partial Human Sketches
Guoyao Su, Yonggang Qi, Kaiyue Pang, Jie Yang and Yi-Zhe Song.
The 31st British Machine Vision Virtual Conference (BMVC2020)
Oral Presentation, 5% acceptance rate
[ Paper ]--[ Github Code ]

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S3NET: Graph Representational Network For Sketch Recognition
Lan Yang, Aneeshan Sain, Linpeng Li, Yonggang Qi, Honggang Zhang and Yi-Zhe Song.
2020 IEEE International Conference on Multimedia and Expo (ICME2020)
[ Paper ]--[ Github Code ]

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Improved Traffic Sign Detection In Videos Through Reasoning Effective RoI Proposals
Yanting Zhang, Yonggang Qi, Jie Yang and Jenq-Neng Hwang.
2020 IEEE International Conference on Multimedia and Expo (ICME2020)
[ Paper ]

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Sketch Fewer to Recognize More by Learning A Co-regularized Sparse Representation
Yonggang Qi and Yi-Zhe Song.
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
[ Paper ]

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Unpaired Image-to-Sketch Translation Network for Sketch Synthesis
Yue Zhang, Guoyao Su, Yonggang Qi and Jie Yang.
IEEE Visual Communications and Image Processing (VCIP), 2019.
[ Paper ]

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SketchSegNet+: An End-to-End Learning of RNN for Multi-Class Sketch Semantic Segmentation
Yonggang Qi and Zheng-Hua Tan.
IEEE ACCESS.
[ Paper ]--[ Dataset download ]

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Image Retrieval by Dense Caption Reasoning
Xinru Wei, Yonggang Qi, Jun Liu and Fang Liu.
IEEE Visual Communications and Image Processing (VCIP), 2017. Oral
[ Paper ]

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Instance-level Coupled Subspace Learning for Fine-grained Sketch-based Image Retrieval
Peng Xu, Qiyue Yin, Yonggang Qi, Yi-Zhe Song, Zhanyu Ma, Liang Wang and Jun Guo.
European Conference on Computer Vision (ECCV), Workshop on Visual Analysis of Sketches, 2016. Oral
[ Paper ]

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Sketch-based Image Retrieval via Siamese Convolutional Neural Network
Yonggang Qi, Yi-Zhe Song, Honggang Zhang and Jun Liu.
IEEE International Conference on Image Processing (ICIP), 2016.
[ Paper ]

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Making Better Use of Edges via Perceptual Grouping
Yonggang Qi, Yi-Zhe Song, Tao Xiang, Honggang Zhang, Timothy Hospedales, Yi Li and Jun Guo.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
[ Paper ]--[ Github Code ]

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Im2Sketch: Sketch generation by unconflicted perceptual grouping
Yonggang Qi, Jun Guo, Yi-Zhe Song, Tao Xiang, Honggang Zhang and Zheng-Hua Tan.
Neurocomputing
[ Paper ]

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sketching by perceptual grouping
Yonggang Qi, Jun Guo, Yi Li, Honggang Zhang, Tao Xiang and Yi-Zhe Song.
IEEE International Conference on Image Processing (ICIP), 2013.
[ Paper ]

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