Results 101 to 110 of about 8,410,900 (380)
Data Mining for Action Recognition [PDF]
, 2015 In recent years, dense trajectories have shown to be an efficient representation for action recognition and have achieved state-of-the-art results on a variety of increasingly difficult datasets. However, while the features have greatly improved the recognition scores, the training process and machine learning used hasn’t in general deviated from the ...
Gilbert, A, Bowden, R
openaire +3 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Kaposiform lymphangiomatosis (KLA) is an aggressive complex lymphatic anomaly. Patients exhibit malformed lymphatic vessels and often develop hemorrhagic effusions and elevated angiopoietin‐2 (Ang‐2) levels. A somatic NRAS p.Q61R (NRASQ61R) mutation has been associated with KLA.
C. Griffin McDaniel +3 more
wiley +1 more source
Weakly supervised instance action recognition
Computational Visual MediaWe study the novel problem of weakly supervised instance action recognition (WSiAR) in multi-person (crowd) scenes. We specifically aim to recognize the action of each subject in the crowd, for which we propose the use of a weakly supervised method ...
Haomin Yan +4 more
doaj +1 more source
SlowFast Based Real-Time Human Motion Recognition with Action Localization [PDF]
, 2023 Gyu-Il Kim, Hyun Yoo, Kyungyong Chung
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Action recognition by dense trajectories [PDF]
CVPR 2011, 2011 Feature trajectories have shown to be efficient for representing videos. Typically, they are extracted using the KLT tracker or matching SIFT descriptors between frames. However, the quality as well as quantity of these trajectories is often not sufficient. Inspired by the recent success of dense sampling in image classification, we propose an approach
Wang, Heng +3 more
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Prevalence and Trajectory of Household Material Hardship Among Children With Advanced Cancer
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background/Objectives Families of children with advanced cancer living in poverty experience inferior outcomes including poor parent mental health and worse child quality of life. Household material hardship (HMH: food, housing, transportation, and/or utility insecurity) is a modifiable poverty exposure—and potential intervention target—that ...
Sarah Wright +13 more
wiley +1 more source
Dilated Multi-Temporal Modeling for Action Recognition
Applied Sciences, 2023 Action recognition involves capturing temporal information from video clips where the duration varies with videos for the same action. Due to the diverse scale of temporal context, uniform size kernels utilized in convolutional neural networks (CNNs ...
Tao Zhang, Yifan Wu, Xiaoqiang Li
doaj +1 more source
Temporal Bilinear Networks for Video Action Recognition
, 2018 Temporal modeling in videos is a fundamental yet challenging problem in computer vision. In this paper, we propose a novel Temporal Bilinear (TB) model to capture the temporal pairwise feature interactions between adjacent frames.
Li, Yanghao +3 more
core +1 more source
Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition [PDF]
Computer Vision and Pattern Recognition, 2019 Skeleton-based human action recognition has attracted great interest thanks to the easy accessibility of the human skeleton data. Recently, there is a trend of using very deep feedforward neural networks to model the 3D coordinates of joints without ...
Pengfei Zhang +4 more
semanticscholar +1 more source
Feature seeding for action recognition [PDF]
2011 International Conference on Computer Vision, 2011 Progress in action recognition has been in large part due to advances in the features that drive learning-based methods. However, the relative sparsity of training data and the risk of overfitting have made it difficult to directly search for good features. In this paper we suggest using synthetic data to search for robust features that can more easily
Matikainen, Pyry +2 more
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