most citedDRL-ISP: Multi-Objective Camera ISP with Deep Reinforcement Learning

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Flow4D: Leveraging 4D Voxel Network for LiDAR Scene Flow Estimation

Jaeyeul Kim, Jungwan Woo, Ukcheol Shin +2

Understanding the motion states of the surrounding environment is critical for safe autonomous driving. These motion states can be accurately derived from scene flow, which capture…

cs.CV2024

Learning to Control Camera Exposure via Reinforcement Learning

Kyunghyun Lee, Ukcheol Shin, Byeong-Uk Lee

Adjusting camera exposure in arbitrary lighting conditions is the first step to ensure the functionality of computer vision applications. Poorly adjusted camera exposure often lead…

cs.CV2024

Stable Surface Regularization for Fast Few-Shot NeRF

Byeongin Joung, Byeong-Uk Lee, Jaesung Choe +5

This paper proposes an algorithm for synthesizing novel views under few-shot setup. The main concept is to develop a stable surface regularization technique called Annealing Signed…

cs.RO2024

Learning Quadrupedal Locomotion with Impaired Joints Using Random Joint Masking

Mincheol Kim, Ukcheol Shin, Jung-Yup Kim

Quadrupedal robots have played a crucial role in various environments, from structured environments to complex harsh terrains, thanks to their agile locomotion ability. However, th…

cs.CV20221 cited

DRL-ISP: Multi-Objective Camera ISP with Deep Reinforcement Learning

Ukcheol Shin, Kyunghyun Lee, In So Kweon

In this paper, we propose a multi-objective camera ISP framework that utilizes Deep Reinforcement Learning (DRL) and camera ISP toolbox that consist of network-based and convention…