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Found 4 papers, 2 papers with code
Attention Modules Improve Modern Image-Level Anomaly Detection: A DifferNet Case Study
Within (semi-)automated visual inspection, learning-based approaches for assessing visual defects, including deep neural networks, enable the processing of otherwise small defect patterns in pixel size on high-resolution imagery.
Attention Modules Improve Image-Level Anomaly Detection for Industrial Inspection: A DifferNet Case Study
Within (semi-)automated visual industrial inspection, learning-based approaches for assessing visual defects, including deep neural networks, enable the processing of otherwise small defect patterns in pixel size on high-resolution imagery.
Ranked #1 on
Anomaly Detection
on InsPLAD
Generalizable Multi-Camera 3D Pedestrian Detection
We present a multi-camera 3D pedestrian detection method that does not need to train using data from the target scene.
Squeezed Deep 6DoF Object Detection Using Knowledge Distillation
We used the LINEMOD dataset to evaluate the proposed method, and the experimental results show that the proposed method reduces the memory requirement by almost 99\% in comparison to the original architecture with the cost of reducing half the accuracy in one of the metrics.
