1 citations · 1 across the 7 of their papers we have counts for
8 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-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…
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…
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…
Sebra: Debiasing Through Self-Guided Bias Ranking
Adarsh Kappiyath, Abhra Chaudhuri, Ajay Jaiswal +4
Ranking samples by fine-grained estimates of spuriosity (the degree to which spurious cues are present) has recently been shown to significantly benefit bias mitigation, over the t…
Bayesian Detector Combination for Object Detection with Crowdsourced Annotations
Zhi Qin Tan, Olga Isupova, Gustavo Carneiro +2
Acquiring fine-grained object detection annotations in unconstrained images is time-consuming, expensive, and prone to noise, especially in crowdsourcing scenarios. Most prior obje…