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Dongjiang Li

5 accepted papers

2026

RealAppiance: Let High-fidelity Appliance Assets Controllable and Workable as Aligned Real Manauls

CVPR 2026

Existing appliance assets suffer from poor rendering, incomplete mechanisms, and misalignment with manuals, leading to simulation-reality gaps that hinder appliance manipulation development. In this work, we introduce the RealAppliance dataset, comprising 100 high-fidelity appliances with complete p

Cited by 0SourceScholar
2025

End-to-End HOI Reconstruction Transformer with Graph-based Encoding

CVPR 2025highlight

Human-object interaction (HOI) reconstruction has garnered significant attention due to its diverse applications and the success of capturing human meshes. Existing HOI reconstruction methods often rely on explicitly modeling interactions between humans and objects. However, such a way leads to a na…

Cited by 0SourcePDFScholar
2021

RaP-Net: A Region-wise and Point-wise Weighting Network to Extract Robust Features for Indoor Localization

IROS 2021poster

Feature extraction plays an important role in visual localization. Unreliable features on dynamic objects or repetitive regions will interfere with feature matching and challenge indoor localization greatly. To address the problem, we propose a novel network, RaP-Net, to simultaneously predict regio…

Cited by 7SourcecodeScholar
2020

Are We Ready for Service Robots? The OpenLORIS-Scene Datasets for Lifelong SLAM

ICRA 2020poster

Service robots should be able to operate autonomously in dynamic and daily changing environments over an extended period of time. While Simultaneous Localization And Mapping (SLAM) is one of the most fundamental problems for robotic autonomy, most existing SLAM works are evaluated with data sequence…

Cited by 174SourcecodeScholar
2020

DXSLAM: A Robust and Efficient Visual SLAM System with Deep Features

IROS 2020poster

A robust and efficient Simultaneous Localization and Mapping (SLAM) system is essential for robot autonomy. For visual SLAM algorithms, though the theoretical framework has been well established for most aspects, feature extraction and association is still empirically designed in most cases, and can…

Cited by 155SourcecodeScholar