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02/11/2023
UGAE: A Novel Approach to Non-exponential Discounting
The discounting mechanism in Reinforcement Learning determines the relat...
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09/19/2022
Understanding reinforcement learned crowds
Simulating trajectories of virtual crowds is a commonly encountered task...
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03/07/2022
A Survey on Reinforcement Learning Methods in Character Animation
Reinforcement Learning is an area of Machine Learning focused on how age...
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09/17/2021
What we see and What we don't see: Imputing Occluded Crowd Structures from Robot Sensing
We consider the navigation of mobile robots in crowded environments, for...
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08/27/2021
A Perceptually-Validated Metric for Crowd Trajectory Quality Evaluation
Simulating crowds requires controlling a very large number of trajectori...
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04/29/2021
Crowd against the machine: A simulation-based benchmark tool to evaluate and compare robot capabilities to navigate a human crowd
The evaluation of robot capabilities to navigate human crowds is essenti...
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03/24/2021
Tracking Pedestrian Heads in Dense Crowd
Tracking humans in crowded video sequences is an important constituent o...
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10/02/2020
OpenTraj: Assessing Prediction Complexity in Human Trajectories Datasets
Human Trajectory Prediction (HTP) has gained much momentum in the last y...
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05/23/2019
Data-Driven Crowd Simulation with Generative Adversarial Networks
This paper presents a novel data-driven crowd simulation method that can...
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04/20/2019
Social Ways: Learning Multi-Modal Distributions of Pedestrian Trajectories with GANs
This paper proposes a novel approach for predicting the motion of pedest...
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09/16/2014