Torr, Philip H. S.

The StarCraft Multi-Agent Challenge

Samvelyan, M., Rashid, T., Schroeder de Witt, C., Farquhar, G., Nardelli, N., Rudner, T. G. J., Hung, C.-M., Torr, P. H. S., Foerster, J., & Whiteson, S. (2019) · International Joint Conference on Autonomous Agents and Multiagent Systems

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 453

The Problem of Degeneracy in Structure and Motion Recovery from Uncalibrated Image Sequences

Torr, P. H. S., Fitzgibbon, A. W., & Zisserman, A. (1999) · International Journal of Computer Vision

Advanced Vision and ImagingRobotics and Sensor-Based Localization

Cited by 156

Solving Inefficiency of Self-supervised Representation Learning

Wang, G., Wang, K., Wang, G., Torr, P. H. S., & Lin, L. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 65

OASIS: Open Agent Social Interaction Simulations with One Million Agents

Yang, Z., Zhang, Z., Zheng, Z., Jiang, Y., Gan, Z., Wang, Z., Ling, Z., Chen, J., Ma, M., Dong, B., et al. (2024) · arXiv

Opinion Dynamics and Social InfluenceMulti-Agent Systems and Negotiation

Cited by 3

Near to Mid-term Risks and Opportunities of Open-Source Generative AI

Eiras, F., Petrov, A., Vidgen, B., de Witt, C. S., Pizzati, F., Elkins, K., Mukhopadhyay, S., Bibi, A., Csaba, B., Steibel, F., et al. (2024) · arXiv

Ethics and Social Impacts of AILaw, AI, and Intellectual Property

Cited by 2