7 papers
GeoMAD: Geometry-Aware Multi-View Anomaly Detection via Deformable Fusion and Distributional Alignment
Shang-Fu Chen, Jhih-Ciang Wu, Kuan-Chuan Peng +2
Multi-view anomaly detection (MvAD) detects defects by exploiting complementary observations from multiple camera viewpoints. The central challenge is to fuse views with sufficient…
See More, Detect Less? Taming Information Leakage in Multi-View Anomaly Detection
Shang-Fu Chen, Kuan-Chuan Peng, Jhih-Ciang Wu +2
In multi-view anomaly detection, more cross-view information can actually hurt. When multiple inspection views are naively fused in a reconstruction-based pipeline, normal cues fro…
TinyFormer: Preserving Tiny Objects in YOLO-DETR Hybrid Real-time Detectors
Jun-Wei Hsieh, Meng-Yu Kao, Ghufron Wahyu Kurniawan +1
YOLO-series and DETR-based detectors struggle with tiny-object detection. YOLO-style models benefit from efficient dense prediction, but their large-stride backbones may suppress t…
Partial Ring Scan: Revisiting Scan Order in Vision State Space Models
Yi-Kuan Hsieh, Kuan-Chuan Peng, Xin li +3
State Space Models (SSMs) have emerged as efficient alternatives to attention for vision tasks, offering lineartime sequence processing with competitive accuracy. Vision SSMs, howe…
PF3Det: A Prompted Foundation Feature Assisted Visual LiDAR 3D Detector
Kaidong Li, Tianxiao Zhang, Kuan-Chuan Peng +1
3D object detection is crucial for autonomous driving, leveraging both LiDAR point clouds for precise depth information and camera images for rich semantic information. Therefore,…
Towards Zero-shot 3D Anomaly Localization
Yizhou Wang, Kuan-Chuan Peng, Yun Fu
3D anomaly detection and localization is of great significance for industrial inspection. Prior 3D anomaly detection and localization methods focus on the setting that the testing…
Long-Tailed Anomaly Detection with Learnable Class Names
Chih-Hui Ho, Kuan-Chuan Peng, Nuno Vasconcelos
Anomaly detection (AD) aims to identify defective images and localize their defects (if any). Ideally, AD models should be able to detect defects over many image classes; without r…