Kim Tran — accepted AI-conference papers

2024

Z-GMOT: Zero-shot Generic Multiple Object Tracking

Kim Tran, Anh Duy Le Dinh, Tien-Phat Nguyen, Thinh Phan, Pha Nguyen, Khoa Luu +3

NAACL 2024findings

Despite recent significant progress, Multi-Object Tracking (MOT) faces limitations such as reliance on prior knowledge and predefined categories and struggles with unseen objects. To address these issues, Generic Multiple Object Tracking (GMOT) has emerged as an alternative approach, requiring less…

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2020

Autonomous Navigation in Complex Environments with Deep Multimodal Fusion Network

Anh Nguyen, Ngoc Nguyen, Kim Tran, Erman Tjiputra, Quang D. Tran

IROS 2020poster

Autonomous navigation in complex environments is a crucial task in time-sensitive scenarios such as disaster response or search and rescue. However, complex environments pose significant challenges for autonomous platforms to navigate due to their challenging properties: constrained narrow passages,…

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