activity
20192026
most citedSimultaneous Mapping and Target Driven Navigation

11 citations · 20 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2026

RoadVGGT: Road-Structure-Aware Feed-Forward Road Surface Reconstruction

Han Jiao, Chen Liu, Jiakai Sun +6

Large-scale road surface reconstruction supports high-definition mapping, autonomous-driving perception, annotation, and simulation. Existing road-specialized optimization methods…

cs.CV2025

RepText: Rendering Visual Text via Replicating

Haofan Wang, Yujia Xu, Yimeng Li +5

Although contemporary text-to-image generation models have achieved remarkable breakthroughs in producing visually appealing images, their capacity to generate precise and flexible…

cs.CV2023

Labeling Indoor Scenes with Fusion of Out-of-the-Box Perception Models

Yimeng Li, Navid Rajabi, Sulabh Shrestha +2

The image annotation stage is a critical and often the most time-consuming part required for training and evaluating object detection and semantic segmentation models. Deployment o…

cs.RO2022

Comparison of Model-Free and Model-Based Learning-Informed Planning for PointGoal Navigation

Yimeng Li, Arnab Debnath, Gregory J. Stein +1

In recent years several learning approaches to point goal navigation in previously unseen environments have been proposed. They vary in the representations of the environments, pro…

cs.RO2022★ 1 cited

Learning-Augmented Model-Based Planning for Visual Exploration

Yimeng Li, Arnab Debnath, Gregory Stein +1

We consider the problem of time-limited robotic exploration in previously unseen environments where exploration is limited by a predefined amount of time. We propose a novel explor…

cs.CV2022★ 1 cited

Self-supervised Pre-training for Semantic Segmentation in an Indoor Scene

Sulabh Shrestha, Yimeng Li, Jana Kosecka

The ability to endow maps of indoor scenes with semantic information is an integral part of robotic agents which perform different tasks such as target driven navigation, object se…

cs.RO2022★ 4 cited

Using Unmanned Aerial Systems (UAS) for Assessing and Monitoring Fall Hazard Prevention Systems in High-rise Building Projects

Yimeng Li, Behzad Esmaeili, Masoud Gheisari +2

This study develops a framework for unmanned aerial systems (UASs) to monitor fall hazard prevention systems near unprotected edges and openings in high-rise building projects. A t…

cs.CV2021★ 3 cited

Uncertainty Aware Proposal Segmentation for Unknown Object Detection

Yimeng Li, Jana Kosecka

Recent efforts in deploying Deep Neural Networks for object detection in real world applications, such as autonomous driving, assume that all relevant object classes have been obse…

cs.CV2020

Learning View and Target Invariant Visual Servoing for Navigation

Yimeng Li, Jana Kosecka

The advances in deep reinforcement learning recently revived interest in data-driven learning based approaches to navigation. In this paper we propose to learn viewpoint invariant…

cs.CV2019★ 11 cited

Simultaneous Mapping and Target Driven Navigation

Georgios Georgakis, Yimeng Li, Jana Kosecka

This work presents a modular architecture for simultaneous mapping and target driven navigation in indoors environments. The semantic and appearance stored in 2.5D map is distilled…