Pei Wang

I am an applied scientist with AWS AI Labs, where I work on computer vision and machine learning. I received my Ph.D. degree from UC San Diego, advised by Nuno Vasconcelos.

I have fortunately worked as a research scientist intern at Adobe Research and an applied scientist intern at Amazon AWS.

Email: peiwang062[at]gmail[dot]com, pwwng[at]amazon[dot]com

Email / Google Scholar / Github / LinkedIn

Recent News

[03/2023] One paper was accepted by CVPR2023.
[02/2023] One paper was accepted by T-PAMI.
[11/2022] I have successfully defended my phd thesis.

Research

I am interested in computer vision and machine learning, especially object detection, image segmentation, semi- and self-supervised learning, human-in-the-loop learning, explainable AI, image synthesis, etc.

	Towards Professional Level Crowd Annotation of Expert Domain Data Pei Wang, and Nuno Vasconcelos CVPR, 2023 code / video
	A Generalized Explanation Framework for Visualization of Deep Learning Model Predictions Pei Wang and Nuno Vasconcelos IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2023 paper
	Omni-DETR: Omni-Supervised Object Detection with Transformers Pei Wang, Zhaowei Cai, Hao Yang, Gurumurthy Swaminathan, Nuno Vasconcelos, Bernt Schiele and Stefano Soatto CVPR, 2022 paper / code / video
	A Machine Teaching Framework for Scalable Recognition Pei Wang and Nuno Vasconcelos ICCV, 2021 paper / code / video
	Gradient-Based Algorithms for Machine Teaching Pei Wang, Kabir Nagrecha and Nuno Vasconcelos CVPR, 2021 paper / code / video
	Rethinking and Improving the Robustness of Image Style Transfer Pei Wang, Yijun Li and Nuno Vasconcelos CVPR (Oral, Best paper candidate), 2021 paper / code / video
	IMAGINE: Image Synthesis by Image-Guided Model Inversion Pei Wang, Yijun Li, Krishna Kumar Singh, Jingwan Lu, and Nuno Vasconcelos CVPR, 2021 paper / code / video
	Dynamic Transfer for Multi-Source Domain Adaptation Yunsheng Li, Lu Yuan, Yinpeng Chen, Pei Wang, Nuno Vasconcelos CVPR, 2021 paper / code / video
	Solving Long-tailed Recognition with Deep Realistic Taxonomic Classifier Tz-Ying Wu, Pedro Morgado, Pei Wang, Chih-Hui Ho, and Nuno Vasconcelos ECCV, 2020 paper / code / video
	SCOUT: Self-aware Discriminant Counterfactual Explanations Pei Wang and Nuno Vasconcelos CVPR, 2020 paper / code / video
	Deliberative Explanations: visualizing network insecurities Pei Wang and Nuno Vasconcelos NeurIPS, 2019 paper / code
	Towards Realistic Predictors Pei Wang and Nuno Vasconcelos ECCV (Oral), 2018 paper / code / video
	Context-dependent random walk graph kernels and tree pattern graph matching kernels with applications to action recognition Weiming Hu, Baoxin Wu, Pei Wang, Chunfeng Yuan, Yangxi Li, and Stephen Maybank IEEE Transactions on Image Processing, 2018 paper
	Graph Based Skeleton Motion Representation and Similarity Measurement for Action Recognition Pei Wang Chunfeng Yuan, Weiming Hu, Bing Li and Yanning Zhang ECCV, 2016 paper

Service

Journal Reviewer: T-PAMI, IJCV, T-IP
Conference Reviewer: CVPR23, NeurIPS22, ICML22, CVPR22, ICLR22, NeurIPS21, ICCV21, ICML21, CVPR21, ICLR21, NeurIPS20, ICML20, ECCV20, CVPR20, NeurIPS19, ICCV19, CVPR19

template credit to Jon Barron