J. Amirian, J. Wouter-van-toll, J. Hayet, and . Pettré, Datadriven crowd simulation with generative adversarial networks, Proc. Int. Conf. Computer Animation and Social Agents, pp.7-10, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02134282

J. Bruneau and J. Pettré, EACS: Effective Avoidance Combination Strategy, Computer Graphics Forum, vol.36, pp.108-122, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01392248

S. Curtis, A. Best, and D. Manocha, Menge: A modular framework for simulating crowd movement, Collective Dynamics, vol.1, pp.1-40, 2016.

B. Teofilo, R. Dutra, . Marques, B. Joaquim, C. A. Cavalcante-neto et al., Gradient-based steering for vision-based crowd simulation algorithms, Comput. Graph. Forum, vol.36, pp.337-348, 2017.

A. Golas, R. Narain, and M. C. Lin, Hybrid long-range collision avoidance for crowd simulation, Proc. ACM SIGGRAPH Symp. Interactive 3D Graphics and Games (I3D '13, pp.29-36, 2013.

S. J. Guy, J. Chhugani, S. Curtis, P. Dubey, M. Lin et al., PLEdestrians: A least-effort approach to crowd simulation, Proc. ACM SIGGRAPH/Eurographics Symp. Computer Animation, pp.119-128, 2010.

D. Helbing and P. Molnár, Social force model for pedestrian dynamics, Phys. Rev. E, vol.51, pp.4282-4286, 1995.

M. Kapadia, S. Singh, W. Hewlett, and P. Faloutsos, Egocentric affordance fields in pedestrian steering, Proc. ACM SIGGRAPH Symp. Interactive 3D Graphics and Games, pp.215-223, 2009.

I. Karamouzas, P. Heil, M. H. Pascal-van-beek, and . Overmars, A predictive collision avoidance model for pedestrian simulation, Proc. Int. Workshop on Motion in Games, pp.41-52, 2009.

I. Karamouzas, H. Mark, and . Overmars, A velocity-based approach for simulating human collision avoidance, Proc. Int. Conf. Intelligent Virtual Agents, pp.180-186, 2010.

I. Karamouzas, B. Skinner, and S. J. Guy, Universal power law governing pedestrian interactions, Phys. Rev. Lett, vol.113, pp.1-5, 2014.

M. Peter, D. H. Kielar, A. Biedermann, and . Borrmann, MomenTUMv2: A modular, extensible, and generic agent-based pedestrian behavior simulation framework, 2016.

H. Kang, M. G. Lee, Q. Choi, J. Hong, and . Lee, Group behavior from video: A data-driven approach to crowd simulation, Proc. ACM SIG-GRAPH/Eurographics Symp. Computer Animation, pp.109-118, 2007.

A. Lerner, Y. Chrysanthou, and D. Lischinski, Crowds by example, Comput. Graph. Forum, vol.26, pp.655-664, 2007.

A. López, F. Chaumette, E. Marchand, and J. Pettré, Character navigation in dynamic environments based on optical flow, Comput. Graph. Forum, vol.38, pp.181-192, 2019.

M. Moussaïd, D. Helbing, and G. Theraulaz, How simple rules determine pedestrian behavior and crowd disasters, Proc. National Academy of Science, vol.108, pp.6884-6888, 2011.

R. Narain, A. Golas, S. Curtis, and M. C. Lin, Aggregate dynamics for dense crowd simulation, ACM Trans. Graph, vol.28, p.122, 2009.

J. Ond?ej, J. Pettré, A. Olivier, and S. Donikian, A synthetic-vision based steering approach for crowd simulation, ACM Trans. Graph, vol.29, p.9, 2010.

S. Paris, J. Pettré, and S. Donikian, Pedestrian reactive navigation for crowd simulation: a predictive approach, Comput. Graph. Forum, vol.26, pp.665-674, 2007.

S. Patil, P. Jur, . Van-den, S. Berg, M. C. Curtis et al., Directing crowd simulations using navigation fields, IEEE Trans. Vis. Comput. Graphics, vol.17, pp.244-254, 2010.

N. Pelechano, J. M. Allbeck, and N. I. Badler, Controlling individual agents in high-density crowd simulation, Proc. ACM SIGGRAPH/Eurographics Symp. Computer Animation, pp.99-108, 2007.

S. Pellegrini, J. Gall, L. Sigal, and L. Van-gool, Destination flow for crowd simulation, Proc. European Conf. Computer Vision, pp.162-171, 2012.

J. Pettré, J. Ond?ej, A. Olivier, A. Cretual, and S. Donikian, Experiment-based modeling, simulation and validation of interactions between virtual walkers, Proc. ACM SIGGRAPH/Eurographics Symp. Computer Animation, pp.189-198, 2009.

C. Reynolds, Steering behaviors for autonomous characters, Proc. Game Developers Conf, pp.763-782, 1999.

S. Singh, M. Kapadia, P. Faloutsos, and G. Reinman, An open framework for developing, evaluating, and sharing steering algorithms, Proc. Int. Workshop on Motion in Games, pp.158-169, 2009.

S. Singh, M. Kapadia, P. Faloutsos, and G. Reinman, Steer-Bench: A benchmark suite for evaluating steering behaviors, Computer Animation and Virtual Worlds, vol.20, pp.5-6, 2009.

A. Treuille, S. Cooper, and Z. Popovi?, Continuum crowds, ACM Trans. Graph, vol.25, issue.3, pp.1160-1168, 2006.

P. Jur, . Van-den, S. J. Berg, M. C. Guy, D. Lin et al., Reciprocal n-body collision avoidance, Proc. Int. Symp. Robotics Research, pp.3-19, 2011.

P. Jur, . Van-den, M. C. Berg, D. Lin, and . Manocha, Reciprocal Velocity Obstacles for real-time multi-agent navigation, Proc. IEEE Int. Conf. Robotics and Automation, 1928.

N. Wouter-van-toll, R. Jaklin, and . Geraerts, Towards believable crowds: A generic multi-level framework for agent navigation, Proc. ACM SIGGRAPH Int. Conf. Motion, Interaction and Games, vol.33, pp.1-33, 2015.

R. Wouter-van-toll, R. Triesscheijn, M. Geraerts, R. Kallmann, N. Oliva et al., A comparative study of navigation meshes, Proc. ACM SIGGRAPH Int. Conf. Motion in Games, pp.91-100, 2016.

H. Wang, J. Ond?ej, and C. Sullivan, Path patterns: Analyzing and comparing real and simulated crowds, Proc. ACM SIGGRAPH Symp. Interactive 3D Graphics and Games, pp.49-57, 2016.

T. Weiss, C. Jiang, A. Litteneker, and D. Terzopoulos, Position-based multi-agent dynamics for real-time crowd simulation, Proc. ACM SIGGRAPH Int. Conf. Motion in Games, vol.10, pp.1-10, 2017.

D. Wolinski, S. J. Guy, A. Olivier, M. C. Lin, D. Manocha et al., Parameter estimation and comparative evaluation of crowd simulations, Comput. Graph. Forum, vol.33, pp.303-312, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01059493

B. Yersin, J. Maïm, J. Pettré, and D. Thalmann, Crowd Patches: Populating large-scale virtual environments for real-time applications, Proc. Symp. Interactive 3D Graphics and Games, pp.207-214, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00555638

, Pedestrian fundamental diagrams: Comparative analysis of experiments in different geometries, Ph.D. Dissertation. Forschungszentrum Jülich, 2012.

J. Zhong, W. Cai, L. Luo, and M. Zhao, Learning behavior patterns from video for agent-based crowd modeling and simulation, Autonomous Agents and Multi-Agent Systems, vol.30, pp.990-1019, 2016.