7 papers
SCOPE: Scene-Contextualized Incremental Few-Shot 3D Segmentation
Vishal Thengane, Zhaochong An, Tianjin Huang +5
Incremental Few-Shot (IFS) segmentation aims to learn new categories over time from only a few annotations. Although widely studied in 2D, it remains underexplored for 3D point clo…
DentalX: Context-Aware Dental Disease Detection with Radiographs
Zhi Qin Tan, Xiatian Zhu, Owen Addison +1
Diagnosing dental diseases from radiographs is time-consuming and challenging due to the subtle nature of diagnostic evidence. Existing methods, which rely on object detection mode…
U-Mamba2: Scaling State Space Models for Dental Anatomy Segmentation in CBCT
Zhi Qin Tan, Xiatian Zhu, Owen Addison +1
Cone-Beam Computed Tomography (CBCT) is a widely used 3D imaging technique in dentistry, providing volumetric information about the anatomical structures of jaws and teeth. Accurat…
CLIMB-3D: Continual Learning for Imbalanced 3D Instance Segmentation
Vishal Thengane, Jean Lahoud, Hisham Cholakkal +4
While 3D instance segmentation (3DIS) has advanced significantly, most existing methods assume that all object classes are known in advance and uniformly distributed. However, this…
U-Mamba2-SSL for Semi-Supervised Tooth and Pulp Segmentation in CBCT
Zhi Qin Tan, Xiatian Zhu, Owen Addison +1
Accurate segmentation of teeth and pulp in Cone-Beam Computed Tomography (CBCT) is vital for clinical applications like treatment planning and diagnosis. However, this process requ…
Foundational Models for 3D Point Clouds: A Survey and Outlook
Vishal Thengane, Xiatian Zhu, Salim Bouzerdoum +2
The 3D point cloud representation plays a crucial role in preserving the geometric fidelity of the physical world, enabling more accurate complex 3D environments. While humans natu…