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Heng Fan

Title: Assistant Professor

Department: Computer Science and Engineering

College: College of Engineering

Curriculum Vitae

Curriculum Vitae Link

Education

  • PhD, Stony Brook University, 2021
    Major: Computer Science
    Dissertation: Algorithms and Benchmarks for Robust Visual Object Tracking

Current Scheduled Teaching

CSCE 5218.004Deep LearningSpring 2025
CSCE 6280.002Advanced Topics in Artificial IntelligenceFall 2024
CSCE 5934.805Directed StudyFall 2024
CSCE 6950.805Doctoral DissertationFall 2024
CSCE 6940.805Individual ResearchFall 2024
CSCE 2900.705Special Problems in Computer Science and EngineeringFall 2024

Previous Scheduled Teaching

CSCE 5934.805Directed StudySummer 10W 2024
CSCE 5218.004Deep LearningSpring 2024 SPOT
CSCE 6950.905Doctoral DissertationSpring 2024
CSCE 6940.905Individual ResearchSpring 2024
CSCE 5900.805Special ProblemsSpring 2024
CSCE 6280.002Advanced Topics in Artificial IntelligenceFall 2023 SPOT
CSCE 6950.805Doctoral DissertationFall 2023
CSCE 6940.805Individual ResearchFall 2023
CSCE 5934.805Directed StudySummer 10W 2023
CSCE 5218.004Deep LearningSpring 2023 Syllabus SPOT
CSCE 6950.905Doctoral DissertationSpring 2023
CSCE 6940.920Individual ResearchSpring 2023
CSCE 5900.820Special ProblemsSpring 2023
CSCE 3110.001Data Structures and AlgorithmsFall 2022 Syllabus SPOT
CSCE 6940.805Individual ResearchFall 2022
CSCE 5900.805Special ProblemsFall 2022
CSCE 5218.001Deep LearningSpring 2022 Syllabus SPOT
CSCE 6940.920Individual ResearchSpring 2022
CSCE 3110.001Data Structures and AlgorithmsFall 2021 Syllabus SPOT

Published Intellectual Contributions

    Conference Proceeding

  • Li, Y., Li, Q., Wang, H., Ma, X., Yao, J., Dong, S., Fan, H., Zhang, L. (2024). Beyond MOT: Semantic Multi-object Tracking. European Conference on Computer Vision (ECCV).
  • Gu, X., Fan, H., Huang, Y., Luo, T., Zhang, L. (2024). Context-Guided Spatio-Temporal Video Grounding. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
  • Zheng, J., Fan, H., Zhang, L. (2024). Kernel Adaptive Convolution for Scene Text Detection via Distance Map Prediction. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
  • Lu, Y., Liu, D., Wang, Q., Han, C., Cui, Y., Cao, Z., Zhang, X., Chen, Y., Fan, H. (2024). ProMotion: Prototypes As Motion Learners. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
  • Lin, L., Fan, H., Zhang, Z., Wang, Y., Xu, Y., Ling, H. (2024). Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance. European Conference on Computer Vision (ECCV).
  • Wang, H., Yu, Y., Luo, T., Fan, H., Zhang, L. (2024). MaGIC: Multi-modality Guided Image Completion. International Conference on Learning Representations (ICLR).
  • Yadav, S., Le, T., Dong, S., Fan, H., Yang, Q., Qiu, C., Li, X., Huang, Y. A New Simulation Platform For Learning-Empowered Distributed Sensing. SPIE Defense + Commercial Sensing 2024.
  • Feng, Y., Meng, Z., Clemmer, C., Fan, H., Huang, Y. (2023). A Multi-granularity Decade-Long Geo-Tagged Twitter Dataset for Spatial Computing. ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL).
  • Shen, Y., Gu, X., Xu, K., Fan, H., Wen, L., Zhang, L. (2023). Accurate and Fast Compressed Video Captioning. International Conference on Computer Vision (ICCV).
  • Liu, X., Liu, X., Yi, Z., Zhou, X., Le, T., Zhang, L., Huang, Y., Yang, Q., Fan, H. (2023). PlanarTrack: A Large-scale Challenging Benchmark for Planar Object Tracking. International Conference on Computer Vision (ICCV).
  • Liu, X., Lin, Y., Yang, Q., Fan, H. (2023). Transferable Adversarial Attack on 3D Object Tracking in Point Cloud. International Conference on Multimedia Modeling (MMM).
  • Gu, B., Fan, H., Zhang, L. (2023). Two Birds, One Stone: A Unified Framework for Joint Learning of Image and Video Style Transfers. International Conference on Computer Vision (ICCV).
  • Zhou, W., Fan, H., Luo, T., Zhang, L. (2023). Unsupervised Domain Adaptive Detection with Network Stability Analysis. International Conference on Computer Vision (ICCV).
  • Yi, Z., Blanco, E., Fan, H., Albert, M. (2022). BAPO: A Large-Scale Multimodal Corpus for Ball Possession Prediction in American Football Games. IEEE Conference on Multimedia Information Processing and Retrieval (MIPR).
  • Guo, M., Zhang, Z., Fan, H., Jing, L. (2022). Divert More Attention to Vision-Language Tracking. Thirty-Sixth Annual Conference on Neural Information Processing Systems (NeurIPS).
  • Yu, Y., Zhang, L., Fan, H., Luo, T. (2022). High-Fidelity Image Inpainting with GAN Inversion. European Conference on Computer Vision (ECCV).
  • Guo, M., Zhang, Z., Fan, H., Jing, L., Lyu, Y., Li, B., Hu, W. (2022). Learning Target-aware Representation for Visual Tracking via Informative Interactions. International Joint Conference on Artificial Intelligence (IJCAI).
  • Lin, L., Fan, H., Zhang, Z., Xu, Y., Ling, H. (2022). SwinTrack: A Simple and Strong Baseline for Transformer Tracking. Thirty-Sixth Annual Conference on Neural Information Processing Systems (NeurIPS).
  • Fan, H., Ling, H. (2021). CRACT: Cascaded Regression-Align-Classification for Robust Tracking. 7013-7020. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  • Fan, H., Ling, H. (2021). MART: Motion-Aware Recurrent Neural Network for Robust Visual Tracking. 566-575. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
  • Singh, Y., Atulkar, V., Ren, J., Yang, J., Fan, H., Latecki, L., Ling, H. (2021). Osteoporosis Prescreening and Bone Mineral Density Prediction using Dental Panoramic Radiographs. 2700-2703. IEEE Engineering in Medicine & Biology Society (EMBC).
  • Fan, H., Yang, F., Chu, P., Lin, Y., Yuan, L., Ling, H. (2021). TracKlinic: Diagnosis of Challenge Factors in Visual Tracking. 970-979. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
  • Fan, H., Miththanthaya, H., Rajan, S., Liu, X., Zou, Z., Lin, Y., Ling, H. (2021). Transparent Object Tracking Benchmark. 10734-10743. IEEE/CVF International Conference on Computer Vision (ICCV).
  • Journal Article

  • Zuo, X., Qi, C., Chen, Y., Shen, J., Fan, H., Yang, W. (2024). Learnable Cross-Scale Sparse Attention Guided Feature Fusion for UAV Object Detection. IEEE Access. 12 114212-114226.
  • Shen, J., Chen, Y., Liu, Y., Zuo, X., Fan, H., Yang, W. (2024). ICAFusion: Iterative Cross-Attention Guided Feature Fusion for Multispectral Object Detection. Pattern Recognition. 145 109913.
  • Zhang, L., Gu, X., Li, C., Luo, T., Fan, H. (2024). Local Compressed Video Stream Learning for Generic Event Boundary Detection. International Journal of Computer Vision. 132 1187–1204.
  • Shen, J., Guo, T., Zuo, X., Fan, H., Yang, W. (2024). SSPNet: Scale and Spatial Priors Guided Generalizable and Interpretable Pedestrian Attribute Recognition. Pattern Recognition. 148 110194.
  • Zhang, L., Jiang, L., Ji, R., Fan, H. (2023). PIDray: A Large-scale X-ray Benchmark for Real-World Prohibited Item Detection. International Journal of Computer Vision. 131 3170–3192.
  • Zhang, L., Gao, J., Xiao, Z., Fan, H. (2023). AnimalTrack: A Benchmark for Multi-Animal Tracking in the Wild. International Journal of Computer Vision. 131 496–513.
  • Wang, H., Zhang, L., Fan, H., Luo, T. (2023). Collaborative three-stream transformers for video captioning. 235 103799. Computer Vision and Image Understanding.
  • Liu, Y., Fan, H., Yuan, X., Xiang, J. (2022). GL-GAN: Adaptive Global and Local Bilevel Optimization for Generative Adversarial Network. Pattern Recognition. 123 108375--1.
  • Zhou, Q., Wang, R., Zeng, G., Fan, H., Zheng, G. (2022). Towards bridging the distribution gap: Instance to Prototype Earth Mover’s Distance for distribution alignment. 82 102607. Medical Image Analysis.
  • Zhu, P., Wen, L., Du, D., Bian, X., Fan, H., Hu, Q., Ling, H. (2022). Detection and Tracking Meet Drones Challenge. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44 (11) 7380-7399.
  • Liu, Y., Fan, H., Ni, F., Xiang, J. (2021). ClsGAN: Selective Attribute Editing Model based on Classification Adversarial Network. Neural Networks. 133 220-228.
  • Fan, H., Bai, H., Lin, L., Yang, F., Chu, P., Deng, G., Yu, S., , H., Huang, M., Liu, J., Xu, Y., Liao, C., Yuan, L., Ling, H. (2021). LaSOT: A High-quality Large-scale Single Object Tracking Benchmark. International Journal of Computer Vision. 129 439–461.
  • Jia, J., Elezovikj, S., Fan, H., Yang, S., Liu, J., Guo, W., Tan, C., Ling, H. (2021). Semantic-Aware Label Placement for Augmented Reality in Street View. The Visual Computer. 37 1805-1819.

Contracts, Grants and Sponsored Research

    Grant - Research

  • Huang, Y. (Principal), Li, X. (Co-Principal), Yang, Q. (Co-Principal), Fan, H. (Co-Principal), Qiu, C. (Co-Principal), Wei, Y. (Co-Principal), Baba, A.I. (Supporting), "Intelligent Distributed Sensing," sponsored by Army Research Lab/Northeastern University, Federal, $902266 Funded. (2024 - 2025).
  • Fan, H. (Principal), "Cooperative Perception for Connected Vehicles," sponsored by Toyota Motor Engineering & Manufacturing North America, International, $60000 Funded. (2023 - 2024).
  • Huang, Y. (Principal), Li, X. (Co-Principal), Yang, Q. (Co-Principal), Fan, H. (Co-Principal), Qiu, C. (Co-Principal), Wei, Y. (Co-Principal), Baba, A.I. (Supporting), "Learning Empowered Distributed Sensing," sponsored by Army Research Lab/Northeastern University, Federal, $2069324 Funded. (2023 - 2024).
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Overall
Summative Rating
Challenge and
Engagement Index
Response Rate

out of 5

out of 7
%
of
students responded
  • Overall Summative Rating (median):
    This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
    • The course as a whole was
    • The course content was
    • The instructor’s contribution to the course was
    • The instructor’s effectiveness in teaching the subject matter was
  • Challenge and Engagement Index:
    This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
    • Do you expect your grade in this course to be
    • The intellectual challenge presented was
    • The amount of effort you put into this course was
    • The amount of effort to succeed in this course was
    • Your involvement in course (doing assignments, attending classes, etc.) was
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