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Found 10 papers, 4 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.
Leveraging Previous Facial Action Units Knowledge for Emotion Recognition on Faces
Facial expressions can be very useful for emotion recognition techniques, as these are the biggest transmitters of non-verbal cues capable of being correlated with emotions.
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
InsPLAD: A Dataset and Benchmark for Power Line Asset Inspection in UAV Images
To the best of our knowledge, InsPLAD is the first large real-world dataset and benchmark for power line asset inspection with multiple components and defects for various computer vision tasks, with a potential impact to improve state-of-the-art methods in the field.
Toward unlabeled multi-view 3D pedestrian detection by generalizable AI: techniques and performance analysis
In this context, we investigate two approaches for automatically labeling target data: pseudo-labeling using a supervised detector and automatic labeling using an untrained detector (that can be applied out of the box without any training).
High-Level Context Representation for Emotion Recognition in Images
Previous works have utilized various nonverbal cues to extract features from images and correlate them to emotions.
Multi-Cue Adaptive Emotion Recognition Network
Expressing and identifying emotions through facial and physical expressions is a significant part of social interaction.
STN PLAD: A Dataset for Multi-Size Power Line Assets Detection in High-Resolution UAV Images
A crucial task for the inspection is to detect and classify assets in the power transmission lines.
Ranked #1 on
Object Detection
on STN PLAD
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.
