most citedWiDEVIEW: An UltraWideBand and Vision Dataset for Deciphering Pedestrian-Vehicle Interactions

2 citations · 3 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2025

Lumos3D: A Single-Forward Framework for Low-Light 3D Scene Restoration

Hanzhou Liu, Peng Jiang, Jia Huang +1

Restoring 3D scenes with low-light conditions is challenging, and most existing methods depend on precomputed camera poses and scene-specific optimization, which greatly restricts…

cs.CV2025

Stylos: Multi-View 3D Stylization with Single-Forward Gaussian Splatting

Hanzhou Liu, Jia Huang, Mi Lu +2

We present Stylos, a single-forward 3D Gaussian framework for 3D style transfer that operates on unposed content, from a single image to a multi-view collection, conditioned on a s…

cs.RO2025

GO: The Great Outdoors Multimodal Dataset

Peng Jiang, Kasi Viswanath, Akhil Nagariya +8

The Great Outdoors (GO) dataset is a multi-modal annotated data resource aimed at advancing ground robotics research in unstructured environments. Existing off-road datasets often…

cs.CV2023★ 1 cited

GPT-4V Takes the Wheel: Promises and Challenges for Pedestrian Behavior Prediction

Jia Huang, Peng Jiang, Alvika Gautam +1

Predicting pedestrian behavior is the key to ensure safety and reliability of autonomous vehicles. While deep learning methods have been promising by learning from annotated video…

cs.RO2023★ 2 cited

WiDEVIEW: An UltraWideBand and Vision Dataset for Deciphering Pedestrian-Vehicle Interactions

Jia Huang, Alvika Gautam, Junghun Choi +1

Robust and accurate tracking and localization of road users like pedestrians and cyclists is crucial to ensure safe and effective navigation of Autonomous Vehicles (AVs), particula…

cs.RO2023

Learning Pedestrian Actions to Ensure Safe Autonomous Driving

Jia Huang, Alvika Gautam, Srikanth Saripalli

To ensure safe autonomous driving in urban environments with complex vehicle-pedestrian interactions, it is critical for Autonomous Vehicles (AVs) to have the ability to predict pe…