3 citations · 3 across the 4 of their papers we have counts for
5 papers
Which Terrain Is Better? Preference Learning with VLM Prototypes for Off-Road Traversability Ranking
Ji-Hoon Hwang, Jisung Bae, E-In Son +3
In vision-based off-road navigation, a robot needs to know not only which obstacles to avoid but also which terrain is better. The first is handled by freespace detection or semant…
Feeling Terrain Before Crossing: World Models for Off-Road Navigation
E-In Son, Dong-Wook Kim, Ji-Hoon Hwang +4
Navigation world models plan by foresight, predicting the future that each candidate action sequence produces and selecting the best, rather than mapping observations to actions di…
CanonNav: Disentangling Navigation Behavior from Camera Geometry in Cross-Platform Visual Navigation
Dong-Wook Kim, Ji-Hoon Hwang, E-In Son +2
While visual navigation has advanced through imitation learning from cross-platform demonstrations, fully leveraging such data remains challenging. First, directly learning from im…
From General Vision to Reliable Traversability Estimation: Adapting Vision Foundation Models for Unstructured Outdoor Environments
Ji-Hoon Hwang, Jisung Bae, Dong-Wook Kim +2
Vision-based approaches have become the dominant paradigm for traversability estimation in unstructured outdoor environments, typically adapting vision foundation models (VFMs) via…
How to Relieve Distribution Shifts in Semantic Segmentation for Off-Road Environments
Ji-Hoon Hwang, Daeyoung Kim, Hyung-Suk Yoon +2
Semantic segmentation is crucial for autonomous navigation in off-road environments, enabling precise classification of surroundings to identify traversable regions. However, disti…