no code implementations • 6 Sep 2022 • Igor Borovikov, Karine Levonyan, Jon Rein, Pawel Wrotek, Nitish Victor
The paper proposes a novel approach to the so-called Face-to-Parameters problem (F2P for short), aiming to reconstruct a parametric face from a single image.
no code implementations • 5 Aug 2022 • Igor Borovikov, Karine Levonyan, Jon Rein, Pawel Wrotek, Nitish Victor
The paper proposes a novel approach to the so-called Face-to-Parameters problem (F2P for short), aiming to reconstruct a parametric face from a single image.
1 code implementation • 7 Dec 2019 • Jiachen Yang, Igor Borovikov, Hongyuan Zha
The interpretability of the learned skills show the promise of the proposed method for achieving human-AI cooperation in team sports games.
no code implementations • 25 Jun 2019 • Yunqi Zhao, Igor Borovikov, Jason Rupert, Caedmon Somers, Ahmad Beirami
In recent years, reinforcement learning has been successful in solving video games from Atari to Star Craft II.
2 code implementations • 3 Jun 2019 • Igor Borovikov, Jesse Harder, Michael Sadovsky, Ahmad Beirami
We propose to create such NPC behaviors interactively by training an agent in the target environment using imitation learning with a human in the loop.
no code implementations • 25 Mar 2019 • Yunqi Zhao, Igor Borovikov, Fernando De Mesentier Silva, Ahmad Beirami, Jason Rupert, Caedmon Somers, Jesse Harder, John Kolen, Jervis Pinto, Reza Pourabolghasem, James Pestrak, Harold Chaput, Mohsen Sardari, Long Lin, Sundeep Narravula, Navid Aghdaie, Kazi Zaman
We discuss two fundamental metrics based on which we measure the human-likeness of agents, namely skill and style, which are multi-faceted concepts with practical implications outlined in this paper.
no code implementations • 16 Nov 2018 • Fernando de Mesentier Silva, Igor Borovikov, John Kolen, Navid Aghdaie, Kazi Zaman
The process of playtesting a game is subjective, expensive and incomplete.