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
- Xinjie Li and Huijuan Xu, 2023, "MEID: Mixture-of-Experts with Internal Distillation for Long-Tailed Video Recognition", Thirty-Seven AAAI Conference on Artificial Intelligence (AAAI)
- Zhi Li, Lu He and Huijuan Xu, 2022, "Weakly-Supervised Temporal Action Detection for Fine-Grained Videos with Hierarchical Atomic Actions", European Conference on Computer Vision (ECCV2022)
- Zhekun Luo, Shalini Ghosh, Devin Guillory, Keizo Kato, Trevor Darrell and Huijuan Xu, 2022, "Disentangled Action Recognition with Knowledge Bases", North American Chapter of the Association for Computational Linguistics (NAACL 2022)
- Jin Liu, Chongfeng Fan, Fengyu Zhou and Huijuan Xu, 2022, "Syntax Controlled Knowledge Graph-to-Text Generation with Order and Semantic Consistency", North American Chapter of the Association for Computational Linguistics (NAACL 2022 Findings)
- 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)
Other
