CrowdFormer: Weakly-supervised Crowd counting with Improved Generalizability

H. Idrees, I. Saleemi, C. Seibert, and M. Shah, “Multi-source multi-scale counting in extremely dense crowd images,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2013, pp. 2547–2554

2013

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O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein et al. , “Imagenet large scale visual recognition challenge,” International journal of computer vision , vol. 115, no. 3, pp. 211–252, 2015

2015

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M. Borstel, M. Kandemir, P. Schmidt, M. Rao, K. Rajamani, and F. Hamprecht, “Gaussian process density counting from weak supervision,” in 2016 European Conference on Computer Vision (ECCV) , 2016, pp. 365–380

2016

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Y. Zhang, D. Zhou, S. Chen, S. Gao, and Y. Ma, “Single-image crowd counting via multi-column convolutional neural network,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2016, pp. 589–597

2016

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A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, and I. Polosukhin, “Attention is all you need,” in Advances in Neural Information Processing Systems , 2017, pp. 5998–6008

2017

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H. Idrees, M. Tayyab, K. Athrey, D. Zhang, S. Al-Maadeed, N. Rajpoot, and M. Shah, “Composition loss for counting, density map estimation and localization in dense crowds,” in European Conference on Computer Vision (ECCV) , 2018, pp. 532–546

2018

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Z. Shi, L. Zhang, Y. Liu, X. Cao, Y. Ye, M.-M. Cheng, and G. Zheng, “Crowd counting with deep negative correlation learning,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , 2018, pp. 5382–5390

2018

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D. Sam, N. Sajjan, H. Maurya, and R. Babu, “Almost unsupervised learning for dense crowd counting,” Proceedings of the AAAI Conference on Artificial Intelligence , vol. 33, pp. 8868–8875, 2019

2019

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I. Loshchilov and F. Hutter, “Decoupled weight decay regularization,” in International Conference on Learning Representations, ICLR , 2019

2019

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J. Wan, W. Luo, B. Wu, A. B. Chan, and W. Liu, “Residual regression with semantic prior for crowd counting,” in 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , 2019, pp. 4031–4040

2019

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Z. Ma, X. Wei, X. Hong, and Y. Gong, “Bayesian loss for crowd count estimation with point supervision,” in 2019 IEEE/CVF International Conference on Computer Vision (ICCV) , 2019, pp. 6141–6150

2019

Cited alongside, same era.

Y. Lei, Y. Liu, P. Zhang, and L. Liu, “Towards using count-level weak supervision for crowd counting,” Pattern Recognition , vol. 109, p. 107616, 2020

2020

Cited alongside, same era.

W. Wang, E. Xie, X. Li, D.-P. Fan, K. Song, D. Liang, T. Lu, P. Luo, and L. Shao, “Pyramid vision transformer: A versatile backbone for dense prediction without convolutions,” in IEEE/CVF International Conference on Computer Vision (CVPR) , 2021, pp. 568–578

2021

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Z. Liu, Y. Lin, Y. Cao, H. Hu, Y. Wei, Z. Zhang, S. Lin, and B. Guo, “Swin transformer: Hierarchical vision transformer using shifted windows,” International Conference on Computer Vision (ICCV) , 2021

2021

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G. Sun, Y. Liu, T. Probst, D. Pani Paudel, N. Popovic, and L. Van Gool, “Boosting crowd counting with transformers,” arXiv e-prints , pp. arXiv–2105, 2021

2021

Later among the works it cites.

D. Liang, X. Chen, W. Xu, Y. Zhou, and X. Bai, “TransCrowd: Weakly-supervised crowd counting with transformer,” arXiv preprint arXiv:2104.09116 , 2021

Original

2021

Later among the works it cites.