Modeling Complex Temporal Composition of Actionlets for Activity Prediction

73 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Skeleton-Based Online Action Prediction Using Scale Selection Network (2019, neutral): “[55] designed a predictive accumulative function.”
Prediction of Human Activity by Discovering Temporal Sequence Patterns (2014, unknown): “Index Terms—Activity prediction, causality, context-cue, predictability Ç”
SSNet: Scale Selection Network for Online 3D Action Prediction (2018, unknown): “[37] designed a predictive accumulative function.”
A Discriminative Model with Multiple Temporal Scales for Action Prediction (2014, unknown): “We propose a principled empirical risk minimization formulation for action prediction, which is not discussed in [1,14,9].”
Learning Maximum Margin Temporal Warping for Action Recognition (2013, background): “The temporal structure of an action can also be modeled based on hidden Markov models [10, 11].”
Skeleton based action recognition with convolutional neural network (2015, background): “Temporal dynamics of postures over time can be modeled as a time series problem, which is crucial for sequencebased action recognition [4, 8, 9].”
Enhanced Sequence Matching for Action Recognition from 3D Skeletal Data (2014, unknown): “Hidden Markov Model (HMM) [16–18, 8] and Conditional Random Field (CRF) [19–21] are popular models for this approach.”