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Published in IWDSC (ECCV Workshop), 2022
We introduce CounTr, a novel end-to-end transformer approach for crowd counting and density estimation, which enables capture global context in every layer of the Transformer.
Recommended citation: Bai, H., He, H., Peng, Z., Dai, T., Chan, SH.G. (2023). CounTr: An End-to-End Transformer Approach for Crowd Counting and Density Estimation. In: Karlinsky, L., Michaeli, T., Nishino, K. (eds) Computer Vision – ECCV 2022 Workshops. ECCV 2022. Lecture Notes in Computer Science, vol 13806. Springer, Cham. https://doi.org/10.1007/978-3-031-25075-0_16
Published in CVPR, 2024
We propose MPCount to tackle the problem of regression nature and label ambiguity for single domain generalization for crowd counting.
Recommended citation: Single Domain Generalization for Crowd Counting, Zhuoxuan Peng, S.-H. Gary Chan, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
Published in BEAM (CVPR Workshop), 2025
This study identifies limitations in existing REC benchmarks and introduces Ref-L4, a comprehensive benchmark with diverse objects, longer expressions, and a larger vocabulary, to better evaluate modern REC models.
Recommended citation: Chen, J., Wei, F., Zhao, J., Song, S., Wu, B., Peng, Z., Chan, S.G., & Zhang, H. (2024). Revisiting Referring Expression Comprehension Evaluation in the Era of Large Multimodal Models. 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 513-524.
Published in CVPR, 2026
EMDUL improves mmWave human pose estimation by expanding datasets with pseudo-labeled and LiDAR-translated point clouds, significantly boosting accuracy and generalization.
Recommended citation: Expanding mmWave Datasets for Human Pose Estimation with Unlabeled Data and LiDAR Datasets, Zhuoxuan Peng, Boan Zhu, Xingjian Zhang, Wenying Li, S.-H. Gary Chan, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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