← Search

Hyeongseok Jeon

3 accepted papers

2025

MORDA: A Synthetic Dataset to Facilitate Adaptation of Object Detectors to Unseen Real-Target Domain While Preserving Performance on Real-Source Domain

ICRA 2025

Deep neural network (DNN) based perception models are indispensable in the development of autonomous vehicles (AVs). However, their reliance on large-scale, high-quality data is broadly recognized as a burdensome necessity due to the substantial cost of data acquisition and labeling. Further, the is

Cited by 2SourceScholar
2024

Beyond the Data Imbalance: Employing the Heterogeneous Datasets for Vehicle Maneuver Prediction

ECCV 2024poster

"Predicting the maneuvers of surrounding vehicles is imperative for the safe navigation of autonomous vehicles. However, naturalistic driving datasets tend to be highly imbalanced, with a bias towards the ”going straight” maneuver. Consequently, learning and accurately predicting turning maneuvers p…

2020

SCALE-Net: Scalable Vehicle Trajectory Prediction Network under Random Number of Interacting Vehicles via Edge-enhanced Graph Convolutional Neural Network

IROS 2020poster

Predicting the future trajectory of surrounding vehicles in a randomly varying traffic level is one of the most challenging problems in developing an autonomous vehicle. Since there is no pre-defined number of interacting vehicles participated in, the prediction network has to be scalable with respe…

Cited by 94SourceScholar