Human action recognition: A taxonomy-based survey, updates, and opportunities

MG Morshed, T Sultana, A Alam, YK Lee - Sensors, 2023‏ - mdpi.com
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 …

Image segmentation using deep learning: A survey

S Minaee, Y Boykov, F Porikli, A Plaza… - IEEE transactions on …, 2021‏ - ieeexplore.ieee.org
Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …

Google scanned objects: A high-quality dataset of 3d scanned household items

L Downs, A Francis, N Koenig, B Kinman… - … on Robotics and …, 2022‏ - ieeexplore.ieee.org
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 …

A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets

K Bayoudh, R Knani, F Hamdaoui, A Mtibaa - The Visual Computer, 2022‏ - Springer
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 …

A review of object detection based on deep learning

Y **ao, Z Tian, J Yu, Y Zhang, S Liu, S Du… - Multimedia Tools and …, 2020‏ - Springer
With the rapid development of deep learning techniques, deep convolutional neural
networks (DCNNs) have become more important for object detection. Compared with …

Teaser: Fast and certifiable point cloud registration

H Yang, J Shi, L Carlone - IEEE Transactions on Robotics, 2020‏ - ieeexplore.ieee.org
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 …

Review of multi-view 3D object recognition methods based on deep learning

S Qi, X Ning, G Yang, L Zhang, P Long, W Cai, W Li - Displays, 2021‏ - Elsevier
Abstract Three-dimensional (3D) object recognition is widely used in automated driving,
medical image analysis, virtual/augmented reality, artificial intelligence robots, and other …

View-GCN: View-based graph convolutional network for 3D shape analysis

X Wei, R Yu, J Sun - … of the IEEE/CVF conference on …, 2020‏ - openaccess.thecvf.com
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 …

Computer vision for solid waste sorting: A critical review of academic research

W Lu, J Chen - Waste Management, 2022‏ - Elsevier
Waste sorting is highly recommended for municipal solid waste (MSW) management.
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

A Garcia-Garcia, S Orts-Escolano, S Oprea… - Applied Soft …, 2018‏ - Elsevier
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 …