Self-supervised learning: A succinct review
Abstract Machine learning has made significant advances in the field of image processing.
The foundation of this success is supervised learning, which necessitates annotated labels …
The foundation of this success is supervised learning, which necessitates annotated labels …
Few-shot object detection: A survey
Deep learning approaches have recently raised the bar in many fields, from Natural
Language Processing to Computer Vision, by leveraging large amounts of data. However …
Language Processing to Computer Vision, by leveraging large amounts of data. However …
Deep cross-modal representation learning and distillation for illumination-invariant pedestrian detection
Integrating multispectral data has been demonstrated to be an effective solution for
illumination-invariant pedestrian detection, in particular, RGB and thermal images can …
illumination-invariant pedestrian detection, in particular, RGB and thermal images can …
Improving Object Detection with Selective Self-supervised Self-training
We study how to leverage Web images to augment human-curated object detection
datasets. Our approach is two-pronged. On the one hand, we retrieve Web images by image …
datasets. Our approach is two-pronged. On the one hand, we retrieve Web images by image …
From depth what can you see? Depth completion via auxiliary image reconstruction
Depth completion recovers dense depth from sparse measurements, eg, LiDAR. Existing
depth-only methods use sparse depth as the only input. However, these methods may fail to …
depth-only methods use sparse depth as the only input. However, these methods may fail to …
Attention-guided multitask convolutional neural network for power line parts detection
Power line parts detection refers to the inspection of key parts on transmission lines against
the complex background in aerial images and identifying whether exist anomalies that …
the complex background in aerial images and identifying whether exist anomalies that …
Exploiting learnable joint groups for hand pose estimation
In this paper, we propose to estimate 3D hand pose by recovering the 3D coordinates of
joints in a group-wise manner, where less-related joints are automatically categorized into …
joints in a group-wise manner, where less-related joints are automatically categorized into …
Comparison and ensemble of 2D and 3D approaches for COVID-19 detection in CT images
Detecting COVID-19 in computed tomography (CT) or radiography images has been
proposed as a supplement to the RT-PCR test. We compare slice-based (2D) and volume …
proposed as a supplement to the RT-PCR test. We compare slice-based (2D) and volume …
Incremental multi-target domain adaptation for object detection with efficient domain transfer
Recent advances in unsupervised domain adaptation have significantly improved the
recognition accuracy of CNNs by alleviating the domain shift between (labeled) source and …
recognition accuracy of CNNs by alleviating the domain shift between (labeled) source and …
A multi-task CNN for maritime target detection
In this letter, we construct MaRine ShiP (MRSP-13), a novel dataset containing 37,161 ship
target images belonging to 13 classes with bounding box annotation, and among them there …
target images belonging to 13 classes with bounding box annotation, and among them there …