RGB-D salient object detection: A survey
Salient object detection, which simulates human visual perception in locating the most
significant object (s) in a scene, has been widely applied to various computer vision tasks …
significant object (s) in a scene, has been widely applied to various computer vision tasks …
A brief introduction to weakly supervised learning
ZH Zhou - National science review, 2018 - academic.oup.com
Supervised learning techniques construct predictive models by learning from a large
number of training examples, where each training example has a label indicating its ground …
number of training examples, where each training example has a label indicating its ground …
Specificity-preserving RGB-D saliency detection
RGB-D saliency detection has attracted increasing attention, due to its effectiveness and the
fact that depth cues can now be conveniently captured. Existing works often focus on …
fact that depth cues can now be conveniently captured. Existing works often focus on …
Localizing objects with self-supervised transformers and no labels
Localizing objects in image collections without supervision can help to avoid expensive
annotation campaigns. We propose a simple approach to this problem, that leverages the …
annotation campaigns. We propose a simple approach to this problem, that leverages the …
Intelligent small object detection for digital twin in smart manufacturing with industrial cyber-physical systems
Recently, along with several technological advancements in cyber-physical systems, the
revolution of Industry 4.0 has brought in an emerging concept named digital twin (DT), which …
revolution of Industry 4.0 has brought in an emerging concept named digital twin (DT), which …
Salient object detection in the deep learning era: An in-depth survey
As an essential problem in computer vision, salient object detection (SOD) has attracted an
increasing amount of research attention over the years. Recent advances in SOD are …
increasing amount of research attention over the years. Recent advances in SOD are …
A single stream network for robust and real-time RGB-D salient object detection
Existing RGB-D salient object detection (SOD) approaches concentrate on the cross-modal
fusion between the RGB stream and the depth stream. They do not deeply explore the effect …
fusion between the RGB stream and the depth stream. They do not deeply explore the effect …
Accurate screening of COVID-19 using attention-based deep 3D multiple instance learning
Automated Screening of COVID-19 from chest CT is of emergency and importance during
the outbreak of SARS-CoV-2 worldwide in 2020. However, accurate screening of COVID-19 …
the outbreak of SARS-CoV-2 worldwide in 2020. However, accurate screening of COVID-19 …
Contrast prior and fluid pyramid integration for RGBD salient object detection
The large availability of depth sensors provides valuable complementary information for
salient object detection (SOD) in RGBD images. However, due to the inherent difference …
salient object detection (SOD) in RGBD images. However, due to the inherent difference …
Deeply supervised salient object detection with short connections
Recent progress on saliency detection is substantial, benefiting mostly from the explosive
development of Convolutional Neural Networks (CNNs). Semantic segmentation and …
development of Convolutional Neural Networks (CNNs). Semantic segmentation and …