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Mingquan Zhou

3 accepted papers

2025

FreeMask3D: Zero-Shot Point Cloud Instance Segmentation Without 3D Training

RA-L 2025

Point cloud instance segmentation is crucial for 3D scene understanding in robotics. However, existing methods heavily rely on learning-based approaches that require large amounts of annotated 3D data, resulting in high annotation costs. Therefore, developing cost-effective and data-efficient soluti

Cited by 0SourceScholar
2025

Geometric Feature-Driven Metric Learning for 3D Craniofacial Superimposition

ICASSP 2025accepted

Craniofacial superimposition is a crucial forensic science technique to identify human remains by matching skulls to facial images. However, this task is challenging due to significant morphological differences between skulls and faces, limited paired samples, and high data dimensionality. We propos…

Cited by 0SourceScholar
2025

OV3D-CG: Open-vocabulary 3D Instance Segmentation with Contextual Guidance

ICCV 2025poster

Open-vocabulary 3D instance segmentation (OV-3DIS), which aims to segment and classify objects beyond predefined categories, is a critical capability for embodied AI applications. Existing methods rely on pre-trained 2D foundation models, focusing on instance-level features while overlooking context…