5 papers
ForestSim: A Synthetic Benchmark for Intelligent Vehicle Perception in Unstructured Forest Environments
Pragat Wagle, Zheng Chen, Lantao Liu
Robust scene understanding is essential for intelligent vehicles operating in natural, unstructured environments. While semantic segmentation datasets for structured urban driving…
Navigating the Wild: Pareto-Optimal Visual Decision-Making in Image Space
Durgakant Pushp, Weizhe Chen, Zheng Chen +3
Navigating complex real-world environments requires semantic understanding and adaptive decision-making. Traditional reactive methods without maps often fail in cluttered settings,…
C^2DA: Contrastive and Context-aware Domain Adaptive Semantic Segmentation
Md. Al-Masrur Khan, Zheng Chen, Lantao Liu
Unsupervised domain adaptive semantic segmentation (UDA-SS) aims to train a model on the source domain data (e.g., synthetic) and adapt the model to predict target domain data (e.g…
Context-Generative Default Policy for Bounded Rational Agent
Durgakant Pushp, Junhong Xu, Zheng Chen +1
Bounded rational agents often make decisions by evaluating a finite selection of choices, typically derived from a reference point termed the default policy,' based on previous…
Visual-Geometry GP-based Navigable Space for Autonomous Navigation
Mahmoud Ali, Durgkant Pushp, Zheng Chen +1
Autonomous navigation in unknown environments is challenging and demands the consideration of both geometric and semantic information in order to parse the navigability of the envi…