An end-to-end transformer model for crowd localization

D Liang, W Xu, X Bai - European Conference on Computer Vision, 2022 - Springer
Crowd localization, predicting head positions, is a more practical and high-level task than
simply counting. Existing methods employ pseudo-bounding boxes or pre-designed …
被引用次数：100 相关文章

An End-to-End Transformer Model for Crowd Localization

D Liang, W Xu, X Bai - European Conference on Computer Vision, 2022 - dl.acm.org
Crowd localization, predicting head positions, is a more practical and high-level task than
simply counting. Existing methods employ pseudo-bounding boxes or pre-designed …
[PDF] ecva.net

[PDF][PDF] An End-to-End Transformer Model for Crowd Localization

D Liang, W Xu, X Bai - ecva.net
Crowd localization, predicting head positions, is a more practical and high-level task than
simply counting. Existing methods employ pseudo-bounding boxes or pre-designed …

An End-to-End Transformer Model for Crowd Localization

D Liang, W Xu, X Bai - arXiv preprint arXiv:2202.13065, 2022 - arxiv.org
Crowd localization, predicting head positions, is a more practical and high-level task than
simply counting. Existing methods employ pseudo-bounding boxes or pre-designed …

An End-to-End Transformer Model for Crowd Localization

D Liang, W Xu, X Bai - arXiv e-prints, 2022 - ui.adsabs.harvard.edu
Crowd localization, predicting head positions, is a more practical and high-level task than
simply counting. Existing methods employ pseudo-bounding boxes or pre-designed …