7 papers
CDGP: Contrastive Dual Gaussian Processes for Weakly Supervised Anomaly Segmentation
Seungjun Chu, Seokhee Han, Mateusz Nowak +1
Industrial visual inspection must both decide whether a product is defective and localize the defect, yet pixel-level masks are costly to collect at scale. Most anomaly-segmentatio…
SPARC: Subspace Position-Aware Robust Few-Shot Calibration for Distribution-Shifted Industrial Anomaly Detection
Seokhee Han, Seungjun Chu, Mateusz Nowak +1
Vision-based industrial anomaly detectors are calibrated on one distribution but may be deployed on another that differs in illumination, fixture placement, or sensor characteristi…
RADAR: Relative Angular Divergence Across Representations
Xavier Cadet, Mateusz Nowak, Peter Chin
Machine learning methods rely on data. However, gathering suitable data can be challenging due to availability constraints, cost, or the need for domain expertise. Expanding datase…
ABCD: All Biases Come Disguised
Mateusz Nowak, Xavier Cadet, Peter Chin
Multiple-choice question (MCQ) benchmarks have been a standard evaluation practice for measuring LLMs' ability to reason and answer knowledge-based questions. Through a synthetic N…
VoD-3DGS: View-opacity-Dependent 3D Gaussian Splatting
Mateusz Nowak, Wojciech Jarosz, Peter Chin
Reconstructing a 3D scene from images is challenging due to the different ways light interacts with surfaces depending on the viewer's position and the surface's material. In class…
Trick-GS: A Balanced Bag of Tricks for Efficient Gaussian Splatting
Anil Armagan, Albert Saà -Garriga, Bruno Manganelli +2
Gaussian splatting (GS) for 3D reconstruction has become quite popular due to their fast training, inference speeds and high quality reconstruction. However, GS-based reconstructio…