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[HTML][HTML] A systematic review of the application of camera-based human pose estimation in the field of sport and physical exercise
Human Pose Estimation (HPE) has received considerable attention during the past years,
improving its performance thanks to the use of Deep Learning, and introducing new …
improving its performance thanks to the use of Deep Learning, and introducing new …
[HTML][HTML] Human pose estimation from monocular images: A comprehensive survey
Human pose estimation refers to the estimation of the location of body parts and how they
are connected in an image. Human pose estimation from monocular images has wide …
are connected in an image. Human pose estimation from monocular images has wide …
A survey on video action recognition in sports: Datasets, methods and applications
To understand human behaviors, action recognition based on videos is a common
approach. Compared with image-based action recognition, videos provide much more …
approach. Compared with image-based action recognition, videos provide much more …
Semantic object parsing with graph lstm
By taking the semantic object parsing task as an exemplar application scenario, we propose
the Graph Long Short-Term Memory (Graph LSTM) network, which is the generalization of …
the Graph Long Short-Term Memory (Graph LSTM) network, which is the generalization of …
Articulated human detection with flexible mixtures of parts
We describe a method for articulated human detection and human pose estimation in static
images based on a new representation of deformable part models. Rather than modeling …
images based on a new representation of deformable part models. Rather than modeling …
Joint multi-person pose estimation and semantic part segmentation
Human pose estimation and semantic part segmentation are two complementary tasks in
computer vision. In this paper, we propose to solve the two tasks jointly for natural multi …
computer vision. In this paper, we propose to solve the two tasks jointly for natural multi …
Human parsing with contextualized convolutional neural network
In this work, we address the human parsing task with a novel Contextualized Convolutional
Neural Network (Co-CNN) architecture, which well integrates the cross-layer context, global …
Neural Network (Co-CNN) architecture, which well integrates the cross-layer context, global …
A hierarchical representation for future action prediction
We consider inferring the future actions of people from a still image or a short video clip.
Predicting future actions before they are actually executed is a critical ingredient for enabling …
Predicting future actions before they are actually executed is a critical ingredient for enabling …
Semantic object parsing with local-global long short-term memory
Semantic object parsing is a fundamental task for understanding objects in detail in
computer vision community, where incorporating multi-level contextual information is critical …
computer vision community, where incorporating multi-level contextual information is critical …
Challenges in multi-modal gesture recognition
This paper surveys the state of the art on multimodal gesture recognition and introduces the
JMLR special topic on gesture recognition 2011–2015. We began right at the start of the …
JMLR special topic on gesture recognition 2011–2015. We began right at the start of the …