Anomaly detection is a crucial task across different domains and data types. However,
existing anomaly detection models are often designed for specific domains and modalities …

Industrial anomaly detection (IAD) has garnered significant attention and experienced rapid
development. However the recent development of IAD approach has encountered certain …

Visual Anomaly Detection (VAD) endeavors to pinpoint deviations from the concept of
normality in visual data, widely applied across diverse domains, eg, industrial defect …

Recently 3D anomaly detection a crucial problem involving fine-grained geometry
discrimination is getting more attention. However the lack of abundant real 3D anomaly data …

Automatic anomaly detection based on visual cues holds practical significance in various
domains such as manufacturing and product quality assessment. This paper introduces a …

Visual anomaly detection is essential and commonly used for many tasks in the field of
robotic vision. Recent anomaly detection datasets mainly focus on industrial automated …

Detecting anomalies in images has become a well-explored problem in both academia and
industry. State-of-the-art algorithms are able to detect defects in increasingly difficult settings …

In this paper, we present a Scale-adaptive method for Anti-aliasing Gaussian Splatting (SA-
GS). While the state-of-the-art method Mip-Splatting needs modifying the training procedure …

Recently, 3D Gaussian Splatting, as a novel 3D representation, has garnered attention for its
fast rendering speed and high rendering quality. However, this comes with high memory …

Anomaly localization is a practical technology for improving industrial production line
efficiency. Due to anomalies are manifold and hard to be collected existing unsupervised …