Jungho An — accepted AI-conference papers

2026

Dynamics-Aware Planning Representation for Zero-Shot Reinforcement Learning (Student Abstract)

Jungho An, Taeyoung Kim, Haeun Kim, Dongsoo Har

AAAI 2026technical

Offline Zero-Shot Reinforcement Learning requires an agent to solve unseen tasks using only a fixed offline dataset without explicit rewards. A central challenge is learning representations that capture both high-level long-term planning and low-level physical dynamics. We propose a novel framework,

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2024

Contextrast: Contextual Contrastive Learning for Semantic Segmentation

Changki Sung, Wanhee Kim, Jungho An, Wooju Lee, Hyungtae Lim, Hyun Myung

CVPR 2024poster

Despite great improvements in semantic segmentation challenges persist because of the lack of local/global contexts and the relationship between them. In this paper we propose Contextrast a contrastive learning-based semantic segmentation method that allows to capture local/global contexts and compr…

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