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About

Minh–Triet Tran is a researcher advancing the frontiers of 3D computer vision and retrieval. His work centers on developing intuitive frameworks for searching and interacting with 3D content, with a particular emphasis on bridging the gap between 2D imagery and 3D scene understanding. Tran’s most influential contribution is pioneering the field of 2D image-based 3D scene retrieval, a novel approach that allows users to search for relevant 3D scenes using a simple 2D scene image as a query. This framework, detailed in his 2018 paper (8 citations), offers a more accessible and convenient method for learning, searching, and utilizing 3D data, with potential applications in virtual reality, robotics, and digital libraries. More recently, Tran has contributed to the SHREC GS-3DORC track (2025, 2 citations), focusing on the retrieval of 3D object parts using Gaussian Splatting—a cutting-edge representation that enhances efficiency and realism. His work demonstrates a commitment to making 3D content more searchable and usable, pushing the boundaries of how we interact with complex spatial data.