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Human action recognition: A taxonomy-based survey, updates, and opportunities
Human action recognition systems use data collected from a wide range of sensors to
accurately identify and interpret human actions. One of the most challenging issues for …
accurately identify and interpret human actions. One of the most challenging issues for …
Image segmentation using deep learning: A survey
Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …
applications such as scene understanding, medical image analysis, robotic perception …
Google scanned objects: A high-quality dataset of 3d scanned household items
Interactive 3D simulations have enabled break-throughs in robotics and computer vision, but
simulating the broad diversity of environments needed for deep learning requires large …
simulating the broad diversity of environments needed for deep learning requires large …
A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets
The research progress in multimodal learning has grown rapidly over the last decade in
several areas, especially in computer vision. The growing potential of multimodal data …
several areas, especially in computer vision. The growing potential of multimodal data …
A review of object detection based on deep learning
With the rapid development of deep learning techniques, deep convolutional neural
networks (DCNNs) have become more important for object detection. Compared with …
networks (DCNNs) have become more important for object detection. Compared with …
Teaser: Fast and certifiable point cloud registration
We propose the first fast and certifiable algorithm for the registration of two sets of three-
dimensional (3-D) points in the presence of large amounts of outlier correspondences. A …
dimensional (3-D) points in the presence of large amounts of outlier correspondences. A …
Review of multi-view 3D object recognition methods based on deep learning
Abstract Three-dimensional (3D) object recognition is widely used in automated driving,
medical image analysis, virtual/augmented reality, artificial intelligence robots, and other …
medical image analysis, virtual/augmented reality, artificial intelligence robots, and other …
View-GCN: View-based graph convolutional network for 3D shape analysis
View-based approach that recognizes 3D shape through its projected 2D images has
achieved state-of-the-art results for 3D shape recognition. The major challenge for view …
achieved state-of-the-art results for 3D shape recognition. The major challenge for view …
Computer vision for solid waste sorting: A critical review of academic research
Waste sorting is highly recommended for municipal solid waste (MSW) management.
Increasingly, computer vision (CV), robotics, and other smart technologies are used for MSW …
Increasingly, computer vision (CV), robotics, and other smart technologies are used for MSW …
A survey on deep learning techniques for image and video semantic segmentation
Image semantic segmentation is more and more being of interest for computer vision and
machine learning researchers. Many applications on the rise need accurate and efficient …
machine learning researchers. Many applications on the rise need accurate and efficient …