Shuai Shao (邵帅)
|
Lead Researcher, ByteDance |
Biography
Shuai Shao, currently serving as a Lead Researcher at Bytedance AI Lab Monetization GenAI, is mentored by Dr. Zehuan Yuan. His research endeavors are deeply rooted in the realms of Multimodal Content Understanding and AI-Generated Content. Shuai is particularly passionate about developing robust systems that are applicable in real-world scenarios.
Shuai hails from Changchun, China, and earned his Bachelor of Science degree from Jilin University in 2017. Upon graduation, he embarked on his professional journey at Megvii Research, where he was fortunate to be mentored by Dr. Gang Yu and under the supervision of Dr. Jian Sun.
Shuai has been competing in programming contests since his high school years. He earned a gold medal in the 2013 ACM-ICPC Asia Regional Contest and secured the 19th position in the 2014 ACM-ICPC World Finals. Subsequently, he served as the coach for Jilin University’s ACM-ICPC team until his graduation.
Recent News
- [Dec. 2023] One paper is accepted by AAAI 2024.
- [Apr. 2023] One paper is accepted by SIGIR 2023.
- [Feb. 2022] One paper is accepted by TIP.
- [Apr. 2019] We published a new dataset Objects365: A Large-scale, High-quality Dataset for Object Detection.
- [Mar. 2019] We are organizing a workshop, Detection In the Wild Challenge Workshop 2019, in conjunction with CVPR 2019.
- [Dec. 2018] A micro documentary about me on JSTV (in Chinese). Link
- [May 2018] We published a new dataset CrowdHuman, a benchmark for detecting human in a crowd.
Awards
- Top Winner of WIDER Face in the WIDER Challenge, 2018.
- Top Winner of Places Instance Segmentation in COCO + Places 2017 Challenges, 2017.
- 19th Place of The 2014 ACM-ICPC World Finals, 2014.
- Gold Medal (2nd Place) of The 2013 ACM-ICPC Asia Regional Contest, 2013.
Professional Activities
- Reviewer of IJCV, TIP, CVPR, ICCV, ACM MM.
- Organizer of Detection In the Wild Challenge Workshop (DIW) at CVPR2019.
Publications
Conference
EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE.
Junyi Chen, Guo Longteng, Jia Sun, Shuai Shao, Zehuan Yuan, Liang Lin, Dongyu Zhang.
AAAI, 2024.
MAMO: Fine-Grained Vision-Language Representations Learning with Masked Multimodal Modeling.
Zijia Zhao*, Longteng Guo*, Xingjian He, Shuai Shao, Zehuan Yuan, Jing Liu.
SIGIR, 2023.
Objects365: A large-scale, high-quality dataset for object detection.
Shuai Shao*, Zeming Li*, Tianyuan Zhang*, Chao Peng*, Gang Yu, Xiangyu Zhang, Jing Li, Jian Sun.
ICCV, 2019.
Shape Robust Text Detection with Progressive Scale Expansion Network.
Wenhai Wang*, Enze Xie*, Xiang Li*, Wenbo Hou, Tong Lu, Gang Yu, Shuai Shao.
CVPR, 2019.
Scene Text Detection with Supervised Pyramid Context Network.
Enze Xie*, Yuhang Zang*, Shuai Shao, Gang Yu, Cong Yao, Guangyao Li.
AAAI, 2019.
Repulsion Loss: Detecting Pedestrians in a Crowd.
Xinlong Wang, Tete Xiao, Yuning Jiang, Shuai Shao, Jian Sun, Chunhua Shen.
CVPR, 2018.
Journal
Birds of a Feather Flock Together: Category-Divergence Guidance for Domain Adaptive Segmentation.
Bo Yuan, Danpei Zhao, Shuai Shao, Zehuan Yuan, Changhu Wang.
IEEE Transactions on Image Processing, 2022.
Pre-print
CrowdHuman: A Benchmark for Detecting Human in a Crowd.
Shuai Shao, Zijian Zhao, Boxun Li, Tete Xiao, Gang Yu, Xiangyu Zhang, Jian Sun.
arXiv preprint arXiv:1805.00123, 2018.
Object detection via end-to-end integration of aspect ratio and context aware part-based models and fully convolutional networks.
Bo Li, Tianfu Wu, Shuai Shao, Lun Zhang, Rufeng Chu.
arXiv preprint arXiv:1612.00534, 2016.
*indicates equal contribution.
Links
Research Collaborators:
Mr. Yuning Jiang Zeming Li (黎泽明) Lan-Zhe Guo (郭兰哲) Tianyuan Zhang (张天远) Enze Xie (谢恩泽) Xinlong Wang (王鑫龙) Changhu Wang (王长虎) Longteng Guo (郭龙腾) Changqian Yu (余昌黔) Bo Yuan (苑博) Yiping Bao Feng Wang Limeng Qiao Junyi Chen