activity
20202024
most citedPedestrian Motion Model Using Non-Parametric Trajectory Clustering and Discrete Transition Points

15 citations · 20 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Towards Open Domain Text-Driven Synthesis of Multi-Person Motions

Mengyi Shan, Lu Dong, Yutao Han +5

This work aims to generate natural and diverse group motions of multiple humans from textual descriptions. While single-person text-to-motion generation is extensively studied, it…

cs.RO2022

Planning Paths through Occlusions in Urban Environments

Yutao Han, Youya Xia, Guo-Jun Qi +1

This paper presents a novel framework for planning in unknown and occluded urban spaces. We specifically focus on turns and intersections where occlusions significantly impact navi…

cs.RO2020★ 5 cited

Planning Paths Through Unknown Space by Imagining What Lies Therein

Yutao Han, Jacopo Banfi, Mark Campbell

This paper presents a novel framework for planning paths in maps containing unknown spaces, such as from occlusions. Our approach takes as input a semantically-annotated point clou…

cs.RO2020

DeepSemanticHPPC: Hypothesis-based Planning over Uncertain Semantic Point Clouds

Yutao Han, Hubert Lin, Jacopo Banfi +2

Planning in unstructured environments is challenging -- it relies on sensing, perception, scene reconstruction, and reasoning about various uncertainties. We propose DeepSemanticHP…

cs.RO2020★ 15 cited

Pedestrian Motion Model Using Non-Parametric Trajectory Clustering and Discrete Transition Points

Yutao Han, Rina Tse, Mark Campbell

This paper presents a pedestrian motion model that includes both low level trajectory patterns, and high level discrete transitions. The inclusion of both levels creates a more gen…