1 citations · 1 across the 8 of their papers we have counts for
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RainSD: Rain Style Diversification Module for Image Synthesis Enhancement using Feature-Level Style Distribution
Hyeonjae Jeon, Junghyun Seo, Taesoo Kim +4
Autonomous driving technology nowadays targets to level 4 or beyond, but the researchers are faced with some limitations for developing reliable driving algorithms in diverse chall…
Challenges of YOLO Series for Object Detection in Extremely Heavy Rain: CALRA Simulator based Synthetic Evaluation Dataset
T. Kim, H. Jeon, Y. Lim
Recently, as many studies of autonomous vehicles have been achieved for levels 4 and 5, there has been also increasing interest in the advancement of perception, decision, and cont…
Integrated Path Tracking with DYC and MPC using LSTM Based Tire Force Estimator for Four-wheel Independent Steering and Driving Vehicle
Sungjin Lim, Bilal Sadiq, Yongsik Jin +4
Active collision avoidance system plays a crucial role in ensuring the lateral safety of autonomous vehicles, and it is primarily related to path planning and tracking control algo…
A Study on Quantifying Sim2Real Image Gap in Autonomous Driving Simulations Using Lane Segmentation Attention Map Similarity
Seongjeong Park, Jinu Pahk, Lennart Lorenz Freimuth Jahn +3
Autonomous driving simulations require highly realistic images. Our preliminary study found that when the CARLA Simulator image was made more like reality by using DCLGAN, the perf…