
Safety science: Forward propagation of a push through a row of people
Sina Feldmann, Juliane Adrian

ICCV 2023: Hard No-Box Adversarial Attack on Skeleton-Based Human Action Recognition with Skeleton-Motion-Informed Gradient
Zhengzhi Lu, He Wang, Ziyi Chang, Guoan Yang, Hubert Shum

Journal of Biomecanics: Stepping strategies of young adults undergoing sudden external perturbation from different directions
Thomas Chatagnon, Anne-Hélène Olivier, Ludovic Hoyet, Julien Pettré, Charles Pontonnier

Computer Graphics Forum: Model-based Crowd Behaviors in Human-solution Space
Wei Xiang, He Wang, Yuqing Zhang, Milo K. Yip and Xiaogang Jin

Safety Science 2023: It’s (not) just a matter of terminology: Everyday understanding of “mass panic” and alternative terms
Helena Lügering, Dilek Tepeli, Anna Sieben

SIGGRAPH 2023: RSMT: Real-time Stylized Motion Transition for Characters
Xiangjun Tang, Linjun Wu, He Wang, Bo Hu, Xu Gong, Yuchen Liao, Songnan Li, Qilong Kou, Xiaogang Jin Computer Vision and Pattern Recognition Abstract Styled online in-between motion generation has important application scenarios

D2.1: Internal version of the simulator
This deliverable describes the efforts done during periods 1 and 2 in the Work Package 2 of the CrowdDNA project towards developing a new crowd simulator algorithm tailored to model both macro and micro-level crowd characteristics.

D1.2: Laboratory dataset on large groups
This deliverable describes the efforts made in task T1.3 “Laboratory experiments in large groups”.

D1.1: Laboratory dataset on small groups
This deliverable describes the efforts made in task T1.2 “Laboratory experiments on small groups”. The goal of this task is to conduct experiments under controlled laboratory conditions with individual participants or small groups that help to fulfill the objectives of WP1.