Photo of Huijuan Xu

Huijuan Xu

Assistant Professor

Affiliation(s):

  • School of Electrical Engineering and Computer Science
  • Computer Science and Engineering

Research Areas:

Data Science and Artificial Intelligence; Signal and Image Processing

 
 

 

Education

  • Ph.D., Computer Science, Boston University, 2018

Publications

Journal Articles

  • Huijuan Xu, Abir Das and Kate Saenko, 2019, "Two-stream region convolutional 3d network for temporal activity detection", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 41, (10), pp. 2319-2332

Conference Proceedings

  • Reuben Tan, Huijuan Xu, Kate Saenko and Bryan A Plummer, 2021, "Logan: Latent graph co-attention network for weakly-supervised video moment retrieval", Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision
  • Yinbo Chen, Zhuang Liu, Huijuan Xu, Trevor Darrell and Xiaolong Wang, 2021, "Meta-baseline: exploring simple meta-learning for few-shot learning", Proceedings of the IEEE/CVF International Conference on Computer Vision
  • Baifeng Shi, Qi Dai, Judy Hoffman, Kate Saenko, Trevor Darrell and Huijuan Xu, 2021, "Temporal Action Detection with Multi-level Supervision", Proceedings of the IEEE/CVF International Conference on Computer Vision
  • Baifeng Shi, Judy Hoffman, Kate Saenko, Trevor Darrell and Huijuan Xu, 2020, "Auxiliary Task Reweighting for Minimum-data Learning", Advances in neural information processing systems (NeurIPS2020)
  • Joanna Materzynska, Tete Xiao, Roei Herzig, Xu*, Huijuan, Wang*, Xiaolong, Darrell* and Trevor, 2020, "Something-else: Compositional action recognition with spatial-temporal interaction networks", IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2020), pp. 1049--1059
  • Ximeng Sun, Huijuan Xu and Kate Saenko, 2020, "TwoStreamVAN: Improving Motion Modeling in Video Generation", The IEEE Winter Conference on Applications of Computer Vision (WACV2020)
  • Zhekun Luo, Devin Guillory, Baifeng Shi, Wei Ke, Fang Wan, Trevor Darrell and Huijuan Xu, 2020, "Weakly-Supervised Action Localization with Expectation-Maximization Multi-Instance Learning", European Conference on Computer Vision (ECCV2020)
  • Roei Herzig, Amir Bar, Huijuan Xu, Gal Chechik, Trevor Darrell and Amir Globerson, 2019, "Learning canonical representations for scene graph to image generation", European Conference on Computer Vision (ECCV2020)
  • Yi Zhu, Yanzhao Zhou, Huijuan Xu, Qixiang Ye, David Doermann and Jianbin Jiao, 2019, "Learning instance activation maps for weakly supervised instance segmentation", IEEE Conference on Computer Vision and Pattern Recognition (CVPR2019)
  • Huijuan Xu, Boyang Li, Vasili Ramanishka, Leonid Sigal and Kate Saenko, 2018, "Joint Event Detection and Description in Continuous Video Streams", IEEE Winter Conference on Applications of Computer Vision (WACV2019)
  • Huijuan Xu, Kun He, Bryan A. Plummer, Leonid Sigal, Stan Sclaroff and Kate Saenko, 2018, "Multilevel Language and Vision Integration for Text-to-Clip Retrieval", Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2019)
  • Huijuan Xu, Abir Das and Kate Saenko, 2017, "R-C3D: Region convolutional 3d network for temporal activity detection", International Conference on Computer Vision (ICCV2017)
  • Huijuan Xu and Kate Saenko, 2016, "Ask, attend and answer: Exploring question-guided spatial attention for visual question answering", European Conference on Computer Vision (ECCV2016)
  • Subhashini Venugopalan, Huijuan Xu, Jeff Donahue, Marcus Rohrbach, Raymond Mooney and Kate Saenko, 2014, "Translating videos to natural language using deep recurrent neural networks", Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2015)
  • Zhekun Luo, Shalini Ghosh, Devin Guillory, Keizo Kato, Trevor Darrell and Huijuan Xu, , "Disentangled Action Recognition with Knowledge-bases", Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2022)
  • Jin Liu, Chongfeng Fan, Fengyu Zhou and Huijuan Xu, , "Syntax Controlled Knowledge Graph-to-Text Generation with Order and Semantic Consistency", Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL Findings 2022)

Other

Research Projects

Honors and Awards

Service

Service to Penn State:

Service to External Organizations:

 


 

About

The School of Electrical Engineering and Computer Science was created in the spring of 2015 to allow greater access to courses offered by both departments for undergraduate and graduate students in exciting collaborative research fields.

We offer B.S. degrees in electrical engineering, computer science, computer engineering and data science and graduate degrees (master's degrees and Ph.D.'s) in electrical engineering and computer science and engineering. EECS focuses on the convergence of technologies and disciplines to meet today’s industrial demands.

School of Electrical Engineering and Computer Science

The Pennsylvania State University

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Department of Computer Science and Engineering

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