About the Authors

Baochang Zhang is a full professor with the Institute of Artificial Intelligence, Beihang

University, Beijing, China; and also with Zhongguancun Laboratory, Beijing, China. He

was selected by the Program for New Century Excellent Talents in the University of Min-

istry of Education of China, chosen as the Academic Advisor of the Deep Learning Lab of

Baidu Inc., and was honored as a Distinguished Researcher of Beihang Hangzhou Institute

in Zhejiang Province. His research interests include explainable deep learning, computer

vision, and pattern recognition. His HGPP and LDP methods were state-of-the-art feature

descriptors, with 1234 and 768 Google Scholar citations, respectively, and both “Test-of-

Time” works. His team’s 1-bit methods achieved the best performance on ImageNet. His

group also won the ECCV 2020 Tiny Object Detection, COCO Object Detection, and ICPR

2020 Pollen recognition challenges.

Sheng Xu received a BE in automotive engineering from Beihang University, Beijing,

China. He has a PhD and is currently at the School of Automation Science and Electrical

Engineering, Beihang University, specializing in computer vision, model quantization, and

compression. He has made significant contributions to the field and has published about a

dozen papers as the first author in top-tier conferences and journals such as CVPR, ECCV,

NeurIPS, AAAI, BMVC, IJCV, and ACM TOMM. Notably, he has 4 papers selected as oral

or highlighted presentations by these prestigious conferences. Furthermore, Dr. Xu actively

participates in the academic community as a reviewer for various international journals

and conferences, including CVPR, ICCV, ECCV, NeurIPS, ICML, and IEEE TCSVT.

His expertise has also led to his group’s victory in the ECCV 2020 Tiny Object Detection

Challenge.

Mingbao Lin finished his MS-PhD study and obtained a PhD in intelligence science and

technology from Xiamen University, Xiamen, China in 2022. In 2016, he received a BS

from Fuzhou University, Fuzhou, China. He is currently a senior researcher with the Ten-

cent Youtu Lab, Shanghai, China. His publications on top-tier conferences/journals include:

IEEE TPAMI, IJCV, IEEE TIP, IEEE TNNLS, CVPR, NeurIPS, AAAI, IJCAI, ACM

MM, and more. His current research interests include developing an efficient vision model,

as well as information retrieval.

Tiancheng Wang received a BE in automation from Beihang University, Beijing, China.

He is currently pursuing a PhD with the Institute of Artificial Intelligence, Beihang Univer-

sity. During his undergraduate studies, he was given the Merit Student Award for several

consecutive years, and has received various scholarships including academic excellence and

academic competitions scholarships. He was involved in several AI projects including behav-

ior detection and intention understanding research and unmanned air-based vision platform,

and more. Now his current research interests include deep learning and network compres-

sion; his goal is to explore a high energy-saving model and drive the deployment of neural

networks in embedded devices.

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