Qi Bi

He is a fourth-year PhD student at the Computer Vision Research Group in University of Amsterdam, supervised by Dr. Shaodi You and Prof. Theo Gevers. His current research focus on robust vision in bad weather and domain generalization.

Before that, He got his bachelor (BEng) and master degree (MSc) from Wuhan University in 2017 and 2020, supervised by Prof. Kun Qin and Prof. Gui-song Xia, with a research focus on aerial image representation learning and multiple instance learning.

In early 2020, He did research internship at the Jarvis Research Center, Tencent Youtu Lab, led by Dr. Yefeng Zheng, focusing on retinal image understanding.

Email: q.bi[at]uva[dot]nl; q_bi[at]whu[dot]edu[dot]cn.

Email / CV / Google Scholar / Github

Honors and Awards

Awarded as a top reviewer for NeurIPS2024.

Awarded as an outstanding reviewer for BMVC2024 (166/840).

Awarded as an outstanding reviewer for International Journal of Computer Vision (IJCV) in the year 2023.

Awarded as an outstanding reviewer for CVPR2023 (top 3.3%, 232/7403).

Work multi-rater medical image segmentation was shortlisted for CVPR2021 best paper candidate (top 0.46%, 32/7015).

Work multi-instance medical image diagnosis was shortlisted for MICCAI2021 travel awards.

Multiple journal publications on aerial scene representation learning have been indexed by Essential Science Indicators (ESI) as highly-cited papers.

Awarded as National Excellent Graduate Students by Ministry of Education of the People's Republic of China in 2019.

Professional Activities

Regular reviewer for TPAMI, IJCV, TIP.

Regular reviewer for CVPR, ICCV, ECCV.

Regular reviewer for NeurIPS, ICML, ICLR.

Regular reviewer for AAAI, IJCAI, ACM MM.

IEEE student member with Signal Processing Society.

AAAI member.

Research

His research focuses on learning discriminative, robust and generalizable visual representations for multiple scenarios such as autonomous driving, medical imaging and aerial imaging. Some representative publications are listed below.

	Learning Content-enhanced Mask Transformer for Domain Generalized Urban-scene Segmentation Qi Bi, Shaodi You, Theo Gevers Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024 code Learning domain generalized scene segmentation by content-enhanced mask attention mechanism.
	Learning Generalized Segmentation for Foggy-Scenes by Bi-directional Wavelet Guidance Qi Bi, Shaodi You, Theo Gevers Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024 code Learning scene segmentation that can be generalized to arbitrary unseen foggy target domains from only a clear source domain; the first work for this task.
	Interactive Learning of Intrinsic and Extrinsic Properties for All-day Semantic Segmentation Qi Bi, Shaodi You, Theo Gevers IEEE Transactions on Image Processing (T-IP), 2023 code dataset Learning robust scene semantic segmentation under all-day scenarios; proposing the first all-day semantic segmentation dataset All-day CityScapes.
	Learning Generalized Medical Image Segmentation from Decoupled Feature Queries Qi Bi, Jingjun Yi, Hao Zheng, Wei Ji, Yawen Huang, Yuexiang Li, Yefeng Zheng Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) code Learning domain generalized medical image segmentation by querying from decoupled features; the first work to leverage Vision Transformer for domain generalized medical image segmentation.
	Segment anything is not always perfect: An investigation of sam on different real-world applications Wei Ji, Jingjing Li, Qi Bi, Wenbo Li, Li Cheng CVPR 1st workshop on Vision-based InduStrial InspectiON, 2023 Best paper award code Benchmarking Segment Anything (SAM) on multiple real-world scenarios.
	All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene Classification Qi Bi, Beichen Zhou, Kun Qin, Qinghao Ye, Gui-Song Xia IEEE Transactions on Geoscience and Remote Sensing (T-GRS), 2022 ESI highly-cited paper code Extending deep multiple instance learning into a multi-grain framework while maintaining the same semantic scheme, dubbed as AGOS; learning discriminative aerial scene representation by AGOS.
	Label-efficient Hybrid-supervised Learning for Medical Image Segmentation Junwen Pan, Qi Bi, Yanzhan Yang, Pengfei Zhu, Cheng Bian * : equal contribution Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022 Learning weakly semi-supervised medical image segmentation by the proposed dynamic instance indicator and dynamic co-regularization framework.
	Local semantic enhanced convnet for aerial scene recognition Qi Bi, Kun Qin, Han Zhang, Gui-Song Xia IEEE Transactions on Image Processing (T-IP), 2021 ESI highly-cited paper code Learning aerial scene representation by modeling context-aware class peak response.
	Joint semantic mining for weakly supervised RGB-D salient object detection Jingjing Li, Wei Ji, Qi Bi, Cheng Yan, Miao Zhang, Yongri Piao, Huchuan Lu Advances in Neural Information Processing Systems (NeurIPS), 2021 code dataset Learning weakly-supervised RGB-D salient object detection (SOD) from the image, depth map and image caption; proposing a dataset for caption based SOD dubbed as CapS.
	Local-global dual perception based deep multiple instance learning for retinal disease classification Qi Bi, Shuang Yu, Wei Ji, Cheng Bian, Lijun Gong, Hanruo Liu, Kai Ma, Yefeng Zheng Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021 MICCAI2021 travel awards MICCAI2021 young scientist award candidate Learning retinal diseases from fundus images by local-global representation.
	MIL-ViT: A multiple instance vision transformer for fundus image classification Qi Bi, Xu Sun, Shuang Yu, Kai Ma, Cheng Bian, Munan Ning, Nanjun He, Yawen Huang, Yuexiang Li, Hanruo Liu, Yefeng Zheng Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021, conference version Journal of Visual Communication and Image Representation, 2023, journal version code Learning medical image Transformer by deep multiple instance learning.
	Learning calibrated medical image segmentation via multi-rater agreement modeling Wei Ji, Shuang Yu, Junde Wu, Kai Ma, Cheng Bian, Qi Bi, Jingjing Li, Hanruo Liu, Li Cheng, Yefeng Zheng Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Best paper candidate code Learning medical image segmentation from multiple annotations by multi-rater modeling.
	A multiple-instance densely-connected ConvNet for aerial scene classification Qi Bi, Kun Qin, Zhili Li, Han Zhang, Kai Xu, Gui-Song Xia IEEE Transactions on Image Processing (T-IP), 2020 ESI highly-cited paper code Modeling discriminative aerial scene representation by deep multiple instance learning.

Supervision

Noud Corten, Improved Road Crack Severity Measurement Using Deep Convolutional Networks by Storing Spatial Information, November 2021-August 2022 (completed).

Carlo Airaghi, Multi-Stage Multiscale Training Architecture for Semantic Segmentation of Remote Sensing Images, April 2021- December 2021 (completed).

Silvan Murre, Layout2Land: Semi-Supervised Learning of a Layout and Style Reconfigurable GAN, March 2021-June 2021 (completed).

Teaching

2024 Vision & Autonomous Robotics (UvA, Lecturer)

2024 Computer Vision 1 (UvA, Lecturer)

2024 Computer Vision 2 (UvA, Teaching Assistant)

2023 Computer Vision 1 (UvA, Teaching Assistant)

2023 Computer Vision 2 (UvA, Teaching Assistant)

2022 Computer Vision 1 (UvA, Teaching Assistant)

2021 Computer Vision 1 (UvA, Teaching Assistant)

2020 Computer Vision 1 (UvA, Teaching Assistant)

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