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HTTP/2 200 server: GitHub.com content-type: text/html; charset=utf-8 last-modified: Sat, 06 Dec 2025 15:06:51 GMT access-control-allow-origin: * etag: W/"6934468b-7a2c" expires: Mon, 29 Dec 2025 14:17:36 GMT cache-control: max-age=600 content-encoding: gzip x-proxy-cache: MISS x-github-request-id: 13BD:2685F2:8D835D:9EF0EC:69528B28 accept-ranges: bytes age: 0 date: Mon, 29 Dec 2025 14:07:36 GMT via: 1.1 varnish x-served-by: cache-bom-vanm7210046-BOM x-cache: MISS x-cache-hits: 0 x-timer: S1767017257.586403,VS0,VE200 vary: Accept-Encoding x-fastly-request-id: c8362eea1e75ce3ed0b6b84a1b1a94e869f0729d content-length: 6866 Yonggang Qi's homepage

Yonggang Qi （齐勇刚）

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.

拟招收博士研究生一名（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。正在招收2026年入学硕士考研同学，欢迎联系。

News

2025-09: Two papers (Dense Semantic Matching & Diffusion Inversion) to appear in NeurIPS 2025!
2025-08: I will serve as an Area Chair (AC) for ICLR 2026!
2025-07: One paper (Talking video generation) to appear in ACM MM 2025. Check it here of our GitHub repo.
2025-01: One paper (Video generation) to appear in ICLR 2025.
2024-12: Two papers (Edge detection & Text-to-image generation) to appear in AAAI 2025 including one Oral!
2024-01: One paper (Sketch generation) to appear in ICLR 2024.
2023-03: One paper about explainable ZS-SBIR to appear in CVPR 2023 as a highlight!
2023-01: Our work on vectorized sketch generation with diffusion model to appear in ICLR 2023 (Spotlight).
2022-10: Our work on sketch to image generation using diffusion model is accepted by BMVC 2022.
2022-09: One work about sketch to point cloud generation is accepted by ACCV 2022 (Oral)!
2022-04: Our work Generative Sketch Healing is accepted by IJCV!
2022-04: I am co-organizing the 2nd workshop on Sketching for Human Expressivity (SHE) at ECCV'22!
2021-12: Promoted to an associate professor.
2021-10: One paper on sketch-based 3D shape retrieval (SBSR) with a new fine-grained SBSR dataset got accepted by TIP!
2021-07: One paper on latticed sketch representation for sketch manipulation got accepted by ICCV 2021! Code and pre-trained models are publicly available now.
2021-04: I am co-organizing 1st workshop on Sketching for Human Expressivity (SHE) at ICCV'21!
2021-03: One paper on perceptual reasoning got accepted by CVPR 2021!
2020-11: One journal paper got accepted by IEEE TCSVT.
2020-08: One paper is accepted at BMVC 2020 as oral presentation.
2020-03: Two papers got accepted by IEEE ICME 2020.
2019-12: One journal paper got accepted by IEEE TCSVT.
2019-11: Moved to UK and started my visiting at CVSSP in University of Surrey!
2019-08: One paper got accepted by IEEE VCIP 2019.
2019-05: Got sponsorship from Chinese Scholarship Council (CSC) for visiting SketchX Lab at CVSSP in University of Surrey for one year!

Selected Publications

*: equal contribution

#: corresponding author

Precise Diffusion Inversion: Towards Novel Samples and Few-Step Models

Jing Zuo, Luoping Cui, Chuang Zhu, & Yonggang Qi^#.

The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025).

[ Paper ]--[ Github Code ]

Fuse2Match: Training-Free Fusion of Flow, Diffusion, and Contrastive Models for Zero-Shot Semantic Matching

Jing Zuo, Jiaqi Wang, Yonggang Qi^#, & Yi-Zhe Song.

The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025).

[ Paper ]--[ Github Code ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

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 ]

Im2Sketch: Sketch generation by unconflicted perceptual grouping

Yonggang Qi, Jun Guo, Yi-Zhe Song, Tao Xiang, Honggang Zhang and Zheng-Hua Tan.

Neurocomputing

[ Paper ]

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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