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 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