HGCN-GJS: Hierarchical Graph Convolutional Network with Groupwise Joint Sampling for Trajectory Prediction

S. Pellegrini, A. Ess, K. Schindler, and L. Van Gool, “You’ll never walk alone: Modeling social behavior for multi-target tracking,” in 2009 IEEE 12th International Conference on Computer Vision . IEEE, 2009, pp. 261–268

2009

Earlier work this paper cites.

A. Lerner, Y. Chrysanthou, and D. Lischinski, “Crowds by example,” in Computer Graphics Forum , vol. 26, no. 3. Wiley Online Library, 2007, pp. 655–664

Original

2009

Earlier work this paper cites.

M. Moussaïd, N. Perozo, S. Garnier, D. Helbing, and G. Theraulaz, “The walking behaviour of pedestrian social groups and its impact on crowd dynamics,” PloS one , vol. 5, no. 4, p. e10047, 2010

2010

Earlier work this paper cites.

B. Zhou, X. Tang, and X. Wang, “Coherent filtering: Detecting coherent motions from crowd clutters,” in European Conference on Computer Vision . Springer, 2012, pp. 857–871

2012

Earlier work this paper cites.

A. Alahi, K. Goel, V. Ramanathan, A. Robicquet, L. Fei-Fei, and S. Savarese, “Social LSTM: Human trajectory prediction in crowded spaces,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2016, pp. 961–971

2016

Earlier work this paper cites.

A. Gupta, J. Johnson, L. Fei-Fei, S. Savarese, and A. Alahi, “Social GAN: Socially acceptable trajectories with generative adversarial networks,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 2255–2264

2018

Earlier work this paper cites.

N. Bisagno, B. Zhang, and N. Conci, “Group LSTM: Group trajectory prediction in crowded scenarios,” in The European Conference on Computer Vision Workshops , September 2018

2018

Cited alongside, same era.

A. Sadeghian, V. Kosaraju, A. Sadeghian, N. Hirose, H. Rezatofighi, and S. Savarese, “SoPhie: An attentive GAN for predicting paths compliant to social and physical constraints,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 1349–1358

2019

Cited alongside, same era.

J. Amirian, J.-B. Hayet, and J. Pettré, “Social ways: Learning multi-modal distributions of pedestrian trajectories with GANs,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops , 2019, pp. 0–0

2019

Cited alongside, same era.

B. Ivanovic and M. Pavone, “The Trajectron: Probabilistic multi-agent trajectory modeling with dynamic spatiotemporal graphs,” in Proceedings of the IEEE International Conference on Computer Vision , 2019, pp. 2375–2384

Y. Chen, C. Liu, B. Shi, and M. Liu, “Comogcn: Coherent motion aware trajectory prediction with graph representation,” The 31st British Machine Vision Virtual Conference (BMVC 2020) , 2020

2020

Closest in time.

K. Mangalam, H. Girase, S. Agarwal, K.-H. Lee, E. Adeli, J. Malik, and A. Gaidon, “It is not the journey but the destination: Endpoint conditioned trajectory prediction,” in European Conference on Computer Vision . Springer, 2020, pp. 759–776

2020

Closest in time.

Y. Chen, C. Liu, B. E. Shi, and M. Liu, “Robot navigation in crowds by graph convolutional networks with attention learned from human gaze,” IEEE Robotics and Automation Letters , vol. 5, no. 2, pp. 2754–2761, 2020

2020

Closest in time.

Y. Hu, S. Chen, Y. Zhang, and X. Gu, “Collaborative motion prediction via neural motion message passing,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2020, pp. 6319–6328

2020

Closest in time.