Dataset Card for X Ego CS Links: Paper Github Codebase Homepage (comming soon) Cross Ego Demo (Pistol Round) Note: This demo concats videos in a grid. The original datasets videos are from individual player POV recording. Dataset Summary X Ego CS is a multi agent gameplay video dataset for cross egocentric multi agent video understanding in Counter Strike:2. It contains 124 hours of synchronized first person gameplay footage captured from 45 professional level Counter Strike 2 matches . Each match includes multi player egocentric video streams (POVs from all players) and corresponding state action trajectories , enabling the study of team level tactical reasoning and situational awareness from individual perspectives. The dataset was introduced in the paper: X Ego: Acquiring Team Level Tactical Situational Awareness via Cross Egocentric Contrastive Video Representation Learning Yunzhe Wang, Soham Hans, Volkan Ustun University of Southern California, Institute for Creative Technologies (2025) arXiv:2510.19150 X Ego CS supports research on multi agent representation learning , egocentric video modeling , team tactic analysis , and AI human collaboration in complex 3D environments. Ho…
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