Associate Professor (Tenured)
Department of Computer Science, San Diego State University
San Diego, CA, 92182
Email: xiaobai DOT liu AT sdsu DOT edu
Office: GMCS 531 GMCS 547
Feb, 2024: I will work as an Area Chair for ACM MM'2024
Jan, 2024: Our ground-breaking system , HOMEYE.sdsu.edu makes the NSF I-Corps regional teams! Time to Change, Real Estate!
October, 2023: Our work on detecting roadway in aerial images will appear in ACM Transactions on Multimedia Computing, Communications and Applications
September, 2023: Dr. Liu is now leading the department-wide supercomputer cssc.sdsu.edu which is equipped with multiple A100 GPUs
September, 2023: Our work on learning deep whistle models from raw data without human in the loop was accepted for publication in The Journal of the Acoustical Society of America, the top journal in bioacoustics
June, 2023: The website for our NSF Grant is now up and runnline: wadsim.sdsu.edu,
May, 2023: My doctoral student Pu Li successfully defended his dissertation and received his doctoral degree. Congrats, Dr. Li!
April, 2023: Our work on Stage-wise GAN for whistle extraction was accepted for publication by IEEE Transaction on Multimedia
Feb, 2023: I will work as the Area Chair for ACM MM 2023
Jan, 2022: our work on Silbido profundo, an open source package for detecting odotocete whistles, will appear in the The Journal of the Acoustical Society of America
April, 2022: We received two grants from the University DRI program to purchases GPU clusters and Real Estate Dataset, respectively! Ready to kick off the Real Estate project!
Feb, 2022: I will work as the Area Chair for ACM MM 2022
January, 2022: I will start my one-year Sabbatical Leave from Summer 2022!
October, 2021: We successfully hosted the first International Conference on AI for Real Estate (AIRE). This online meeting attracted more than 500 participants! Real Estate Professionals are welcome for the next year event!
September, 2021: We received a three-year NSF grant (PI) to study safety measures of autonomous vehicles in winter seasons.
April, 2021: Our work on policy-driven image augmentation was accepted as a regular paper by ACM Conference on Multimedia!
April, 2021: Our paper on pose grammar was accepted by TPAMI!
Feb, 2020: I will work as the Area Chair for ACM MM 2021
September, 2020: We received a three-year ONR grant (co-PI) to develop learning-based whistle extraction methods without human in the loop! Second Grant in this direction!
May, 2020: Our paper on call sequence detection was accepted by JRSI!
April, 2020: Our paper on generating adversarial samples using hamiltonian monte carlo method was accepted by TPAMI!
April, 2020: Our paper on learning-based planar homography estimation in aerial videos was accepted for publication in ICPR!
Feburary, 2020: Our paper for Learning-based Whistle Extraction was accepted for publication in IJCNN. New SOTA!
January, 2020: Our paper for marine mammal species detection was accepted for publication in Nature Scientific Reports.
December, 2019: Our paper for whistle detection was accepted for publication in the Nature Scientific Reports.
September, 2019: Our paper for learning composite object part models was published in the IEEE TNNLS.
August, 2019: I received tenure and promotion.
Sep 20, 2018: I will work as an Area Chair for the 2019 ACM Conference on Multimedia.
May 29, 2018: I was invited to work as an Panelist and Grant Reviewer for two National Science Foundation (NSF) Programs! Thanks, NSF!
May 20, 2018: I will work as an Area Chair for the 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR'2019)! Welcome to Long Beach, CA!
May 18, 2018: I was selected as one of the three faculty honorees for the President's Excellence Awards! Thanks, President Roush!
May 4, 2018: I received a Grant (co-PI) from the California Transit Association (Senate Bill 1: Landmark Transportation Funding Package).
May 1, 2018: Our paper on high-precision camera localization in scenes with repretitive patterns was accepted for publication in ACM Transactions on Intelligent Systems and Technology.
March 1, 2018: Our paper on weakly supervised learning for object tracking was accepted for publication in IJCAI'2018.
March 1, 2018: Our paper on visual causality reasoning was accepted for publication in CVPR'2018.
December 1, 2017: Our paper on 3D Human Pose Recognition was accepted as Oral Presentation in the AAAI'2018.
December 1, 2017: Our paper on Visual House Appraisal was accepted for publication in the IEEE Transactions on Knowledge and Data Engineering (TKDE).
October 30, 2017: Our paper on Image Segmentation was accepted for publication in the Journal Pattern Recognition.
September 30, 2017: Our paper on multi-view object tracking was accepted for publication in the IEEE Transactions on Circuits and Systems for Video Technology (CSVT).
August 15, 2017: I received a Grant (co-PI) from the ONR Marine Mammals and Biology Program (PI: Marie Roch).
July 15, 2017: Our paper on Discrete Multi-modal Hashing was accepted for publication in the IEEE Transactions on Multimedia.
July 1, 2017: Our paper on Grayscale-Thermal Tracking was accepted for publication in the IEEE Transactions on Image Processing.
June 15, 2017: Our paper on Place-centric Visual Urban Perception was accepted for publication in the ACM MM'2017.
May 11, 2017: Our paper on knowledge-based 3D scene reconstruction was accepted for publication in the IJCAI'2017.
May 4, 2017: I eceived a Grant (Sole PI) from the NSF CRII program in the area of 3D scene reconstruction and commonsense reasoning!
March 15, 2017: Prof. Takeo Kanade visited the SDSU Computer Vision Lab and gave a talk in Montezuma hall.
April 20, 2017: I will co-organize the ACM Multimedia Workshop on Visual Analatic for Smart and Connected Communities in conjunction with the ACM MM'2017.
Dec. 27 , 2016: One fully funded PhD student position is available. Please contact xiaobai.liu@mail.sdsu.edu for more details.
Dec. 20 , 2016: Our paper on attribute grammar will appear in the IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017.
Dec. 1 , 2016: Our paper on cross-view object tracking was accepted by the AAAI Conference on Artificial Intelligence (AAAI) 2017.
Sep.19, 2016: Call for Paper is available. Welcome to submit your papers or long-abstract.
Sep.12, 2016: We are organizing the AAAI'2017 workshop on AI for Connected and Automated Vehicles (AI-CAV).
June 24, 2016: Our paper will appear in the IEEE Transactions on Knowledge and Data Engineering (TKDE).
June 22, 2016: Our paper on Visual Vehicle-to-Vehicle (V3I) was accpeted as Oral Presentation by ACM MM'2016
May 30, 2016: I will chair the session of Machine Learning8: Data Mining in IJCAI'2016. Welcome to Attend!
Apr. 10, 2016: Our paper on Hierarchical LSTM model for Scene Parsing was accepted by IJCAI'2016.
Apr. 10, 2016: Our paper on Mobile Landmark Search was accepted by IJCAI'2016.
Apr. 10, 2016: Our paper on Single-view 3D Scene Reconstruction was accepted by IJCAI'2016.
Feb. 29, 2016: Our Paper on Multi-view Human Tracking was accepted by IEEE CVPR'2016!
Feb. 24, 2016: Received the SDSU GREW Fellowship Spring 2016.
Feb. 1, 2016: I will chair the sessions of VIS: Pose Estimation and ML: Deep Learning I in AAAI' 2016. Welcome to Attend!
Jan. 10, 2016: Our Proposal to the SDSU Undergraduate Research Program has been awarded. Congradulations to Jacob Thalman!
Jan. 7, 2016: Received a donation of GPU K40 from the NVIDA Inc. Thanks NVIDA!
Dec. 1, 2015: Our paper on Attributed Grammar was accepted by AAAI'2016.
PhD Student 2019-present
PhD student
2021-present
Master student
2021-present
Undergraduate student
2021-present
Master student
2022-present
Master student
2022-present
Master student
2022-present
Master student
2022-present
30. Pu Li, Xiaobai Liu, Xiaohui Xie. Learning Sample-Specific Policies for Sequential Image Augmentation. ACM Conference on Multimedia, 2021.
29. Huijie Zhang, Li An, Vena W Chu, Douglas A Stow, Xiaobai Liu, Qinghua Ding. Learning Adjustable Reduced Downsampling Network for Small Object Detection in Urban Environments. Remote Sensing. 2021
28. Yuanlu Xu, Wenguan Wang, jianwen Xie, Xiaobai Liu, Song-chun Zhu. "Monocular 3D Pose Estimation via Pose Grammar and Data Augmentation". IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
27. Shyam Madhusudhana, Yu Shiu, Holger Klinck, Erica Fleishman, Xiaobai Liu, Eva-Marie Nosal, Tyler Helble, Danielle Cholewiak, Douglas Gillespie, Ana Širović, Marie A. Roch. “Improve detection of call sequences with temporal context”, Journal of the Royal Society Interface, 2021
26. Hongjun Wang, Guanbin Li, Xiaobai Liu, Liang Lin , A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, preprint, 2020
25. Pu Li, Xiaobai Liu, KJ Palmer, Erica Fleishman, Douglas Gillespie, Eva-Marie Nosal, Yu Shiu, Holger Klinck, Danielle Cholewiak, Tyler Helble, Marie A Roch. Learning deep models from synthetic data for extracting dolphin whistle contours. IJCNN, 2020
24. Pu Li, Xiaobai Liu. Learning Knowledge-Rich Sequential Model for Planar Homography Estimation in Aerial Videos. IEEE Conference on Pattern Recognition, 2020
23. Bo Zhao, S. Zhang, C. Xu, Xiaobai Liu. Spoofing in Geography: Can We Trust Artificial Intelligence to Manage Geospatial Data? Spatial Synthesis, 325-338, 2020
22. Pu Li, Xiaobai Liu, K. Palmer, Erica Fleishman, Douglas Gillespie, Eva-Marie Nosal, Yu Shiu, Holger Klinck, Danielle Cholewiak, Tyler Helble and Marie Roch. Learning Deep Models from Synthetic Data for Extracting Dolphin Whistle Contours. International Joint Conference on Neural Networks (IJCNN), 2020
21. Yu Shiu, KJ Palmer, Marie A Roch, Erica Fleishman, Xiaobai Liu, Eva-Marie Nosal, Tyler Helble, Danielle Cholewiak, Douglas Gillespie, Holger Klinck. Deep neural networks for automated detection of marine mammal species, Nature Scientific Reports, 2020
20. Xiaobai Liu, Qian Xu, Shuicheng Yan and Jiebo Luo. Learning Semi-supervised Multi-Label Fully Convolutional Network for Hierarchical Object Parsing”, IEEE Transactions on Neural Network and Learning Systems (TNNLS), 2019
19. Tianshui Chen, Riquan Chen, Lin Nie, Xiaonan Luo, Xiaobai Liu, and Liang Lin. Neural Task Planning with And-Or Graph Representations. IEEE Transactions on Multimedia, 2019
18. Hao-Shu Fang, Yuanlu Xu, Wenguan Wang, Xiaobai Liu, Song-Chun Zhu. Learning Pose Grammar to Encode Human Body Configuration for 3D Pose Estimation, AAAI Conference on Artificial Intelligence (AAAI), 2018
17. Xiaobai Liu, Qian Xu, Jingjie Yang, Jacob Thalman, Shuicheng Yan, and Jiebo Luo. Learning Multi-Instance Deep Ranking and Regression Network for Visual House Appraisal. IEEE Transactions on Knowledge and Data Engineering (TKDE), in press, 2018
16. Kunqian Li, Wenbing Tao, Xiaobai Liu, Liman Liu. Iterative Image Segmentation with Feature Driven Heuristic Four Color Labeling, Pattern Recognition, 2018
15. Xiaobai Liu, Yuanlu Xu, Lei Zhu and Yadong Mu. A Stochastic Attribute Grammar for Robust Cross-View Human Tracking. IEEE Transactions on Circuits and Systems for Video Technology (CSVT), in press, 2018
14. Xiaobai Liu, Qi Chen, Lei Zhu, Yuanlu Xu and Liang Lin. Place-centric Visual Urban Perception with Deep Multi-instance Regression. ACM Conference on Multimedia, accepted, 2017
13. Chengcheng Yu^*, Xiaobai Liu^*, and Song-Chun Zhu. “Reasoning Geometric Commonsense for Single-view 3D Scene Parsing.” International Joint Conference on Artificial Intelligence (IJCAI), accepted, 2017 (Acceptance Rate 24%, ^: equal contributions)
12. Yuanlu Xu, Xiaobai Liu*, Lei Qin and Song-Chun Zhu. “Cross-view People Tracking by Scene-centered Spatio-temporal Parsing.” AAAI Conference on Artificial Intelligence (AAAI), accepted, 2017 (Acceptance Rate 24%)
11. Xiaobai Liu* , Yibiao Zhao and Song-Chun Zhu. “Attributed Grammar for Single-view 3D Scene Reconstruction”. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), in press, 2017
10. Chenglong Li, Hui Cheng, Shiyi Hu, Xiaobai Liu, Jin Tang and Liang Lin. “Learning Collaborative Sparse Representation for Grayscale-Thermal Tracking”. IEEE Transactions on Image Processing, in press, 2016
9. Wenbin Jiang, Min Long, Laurence T. Yang, Xiaobai Liu, Hai Jin, Alan L. Yuille, and Ye Chi. "FIPIP: A novel fine-grained parallel partition based intra-frame prediction on heterogeneous many-core systems." Future Generation Computer Systems, in press, 2016
8. Yadong Mu, Wei Liu, Xiaobai Liu, and Wei Fan. “Stochastic Gradient Made Stable: A Manifold Propagation Approach for Large-Scale Optimization”. IEEE Transactions on Knowledge and Data Engineering, in press, 2016
7. Ping Luo, Xiaobai Liu and Liang Lin. "Learning Compositional Shape Models by Integrating Multiple Distance Metrics". IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 7, page: 1417-1428, 2016
6. Xiaobai Liu*. “V3I-STAL: Visual Vehicle-to-Vehicle Interaction via Simultaneous Tracking and Localization”. ACM Conference on Multimedia (long paper), 2016 (Acceptance Rate: 20%)
5. Xiaobai Liu*. “Multi-view 3D Human Tracking in Crowded Scenes”. Thirtieth AAAI Conference on Artificial Intelligence (AAAI), page: 3553-3559, 2016 (Acceptance Rate: 26%)
4. Xiaobai Liu*, Yadong Mu and Liang Lin. “A Stochastic Grammar for Fine-grained 3D Scene Reconstruction”. International Joint Conference on Artificial Intelligence (IJCAI), page: 3424-3431, 2016 (Acceptance Rate: 25%)
3. Lei Zhu, Jialei Shen, Xiaobai Liu and Liang Xie. “Learning Compact Visual Representation with Canonical Views for Robust Mobile Landmark Search”. International Joint Conference on Artificial Intelligence (IJCAI), page: 3959-3966, 2016 (Acceptance Rate: 25%)
2. Zhanglin Peng, Ruimao Zhang, Xiaodan Liang, Liang Lin, and Xiaobai Liu. “Geometric Scene Parsing with Hierarchical LSTM”. International Joint Conference on Artificial Intelligence (IJCAI), page: 3439-3446, 2016 (Acceptance Rate: 25%)
1. Yuanlu Xu, Xiaobai Liu*, Yang Liu, and Song-Chun Zhu. “Multi-view People Tracking via Hierarchical Trajectory Composition”. IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), page: 4256-4265, 2016 (Acceptance Rate: 29% )