354 citations · 1.1k across the 115 of their papers we have counts for
9 papers · 1 filter
AutoScale: Learning to Scale for Crowd Counting and Localization
Chenfeng Xu, Dingkang Liang, Yongchao Xu +4
Recent works on crowd counting mainly leverage CNNs to count by regressing density maps, and have achieved great progress. In the density map, each person is represented by a Gauss…
UrbanLoco: A Full Sensor Suite Dataset for Mapping and Localization in Urban Scenes
Weisong Wen, Yiyang Zhou, Guohao Zhang +5
Mapping and localization is a critical module of autonomous driving, and significant achievements have been reached in this field. Beyond Global Navigation Satellite System (GNSS),…
Multiple criteria decision-making for lane-change model
Ao Li, Liting Sun, Wei Zhan +1
Simulation has long been an essential part of testing autonomous driving systems, but only recently has simulation been useful for building and training self-driving vehicles. Vehi…
INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps
Wei Zhan, Liting Sun, Di Wang +8
Behavior-related research areas such as motion prediction/planning, representation/imitation learning, behavior modeling/generation, and algorithm testing, require support from hig…
Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving
Jiachen Li, Wei Zhan, Yeping Hu +1
Accurately tracking and predicting behaviors of surrounding objects are key prerequisites for intelligent systems such as autonomous vehicles to achieve safe and high-quality decis…
Interpretable Modelling of Driving Behaviors in Interactive Driving Scenarios based on Cumulative Prospect Theory
Liting Sun, Wei Zhan, Yeping Hu +1
Understanding human driving behavior is important for autonomous vehicles. In this paper, we propose an interpretable human behavior model in interactive driving scenarios based on…
Behavior Planning of Autonomous Cars with Social Perception
Liting Sun, Wei Zhan, Ching-Yao Chan +1
Autonomous cars have to navigate in dynamic environment which can be full of uncertainties. The uncertainties can come either from sensor limitations such as occlusions and limited…
Coordination and Trajectory Prediction for Vehicle Interactions via Bayesian Generative Modeling
Jiachen Li, Hengbo Ma, Wei Zhan +1
Coordination recognition and subtle pattern prediction of future trajectories play a significant role when modeling interactive behaviors of multiple agents. Due to the essential p…
Multi-modal Probabilistic Prediction of Interactive Behavior via an Interpretable Model
Yeping Hu, Wei Zhan, Liting Sun +1
For autonomous agents to successfully operate in real world, the ability to anticipate future motions of surrounding entities in the scene can greatly enhance their safety levels s…