5 papers
Enhancing Policy Learning with World-Action Model
Yuci Han, Alper Yilmaz
This paper presents the World-Action Model (WAM), an action-regularized world model that jointly reasons over future visual observations and the actions that drive state transition…
BetterScene: 3D Scene Synthesis with Representation-Aligned Generative Model
Yuci Han, Charles Toth, John E. Anderson +2
We present BetterScene, an approach to enhance novel view synthesis (NVS) quality for diverse real-world scenes using extremely sparse, unconstrained photos. BetterScene leverages…
UAS Visual Navigation in Large and Unseen Environments via a Meta Agent
Yuci Han, Charles Toth, Alper Yilmaz
The aim of this work is to develop an approach that enables Unmanned Aerial System (UAS) to efficiently learn to navigate in large-scale urban environments and transfer their acqui…
UAS Navigation in the Real World Using Visual Observation
Yuci Han, Jianli Wei, Alper Yilmaz
This paper presents a novel end-to-end Unmanned Aerial System (UAS) navigation approach for long-range visual navigation in the real world. Inspired by dual-process visual navigati…
Learning to Drive Using Sparse Imitation Reinforcement Learning
Yuci Han, Alper Yilmaz
In this paper, we propose Sparse Imitation Reinforcement Learning (SIRL), a hybrid end-to-end control policy that combines the sparse expert driving knowledge with reinforcement le…