Activity Recognition

139 papers with code • 1 benchmarks • 20 datasets

Human Activity Recognition is the problem of identifying events performed by humans given a video input. It is formulated as a binary (or multiclass) classification problem of outputting activity class labels. Activity Recognition is an important problem with many societal applications including smart surveillance, video search/retrieval, intelligent robots, and other monitoring systems.

Source: Learning Latent Sub-events in Activity Videos Using Temporal Attention Filters

Greatest papers with code

AssembleNet++: Assembling Modality Representations via Attention Connections

google-research/google-research 18 Aug 2020

We create a family of powerful video models which are able to: (i) learn interactions between semantic object information and raw appearance and motion features, and (ii) deploy attention in order to better learn the importance of features at each convolutional block of the network.

Action Classification Activity Recognition

AdaRNN: Adaptive Learning and Forecasting of Time Series

jindongwang/transferlearning 10 Aug 2021

This paper proposes Adaptive RNNs (AdaRNN) to tackle the TCS problem by building an adaptive model that generalizes well on the unseen test data.

Activity Recognition Time Series

Cross-domain Activity Recognition via Substructural Optimal Transport

jindongwang/transferlearning 29 Jan 2021

In this paper, we propose substructure-level matching for domain adaptation (SSDA) to better utilize the locality information of activity data for accurate and efficient knowledge transfer.

Cross-Domain Activity Recognition Domain Adaptation +1

Large-scale weakly-supervised pre-training for video action recognition

microsoft/computervision-recipes CVPR 2019

Second, frame-based models perform quite well on action recognition; is pre-training for good image features sufficient or is pre-training for spatio-temporal features valuable for optimal transfer learning?

Ranked #2 on Egocentric Activity Recognition on EPIC-KITCHENS-55 (Actions Top-1 (S2) metric)

Action Classification Action Recognition +3

Feature engineering workflow for activity recognition from synchronized inertial measurement units

blue-yonder/tsfresh 18 Dec 2019

The ubiquitous availability of wearable sensors is responsible for driving the Internet-of-Things but is also making an impact on sport sciences and precision medicine.

Activity Recognition Feature Engineering +2

Deep Residual Bidir-LSTM for Human Activity Recognition Using Wearable Sensors

guillaume-chevalier/LSTM-Human-Activity-Recognition 22 Aug 2017

Human activity recognition (HAR) has become a popular topic in research because of its wide application.

Activity Recognition

PoseTrack: A Benchmark for Human Pose Estimation and Tracking

open-mmlab/mmpose CVPR 2018

In this work, we aim to further advance the state of the art by establishing "PoseTrack", a new large-scale benchmark for video-based human pose estimation and articulated tracking, and bringing together the community of researchers working on visual human analysis.

Activity Recognition Multi-Person Pose Estimation +1

Multivariate LSTM-FCNs for Time Series Classification

timeseriesAI/tsai 14 Jan 2018

Over the past decade, multivariate time series classification has received great attention.

Action Recognition Classification +3

Deep learning for time series classification

hfawaz/dl-4-tsc 1 Oct 2020

In this context, deep learning has emerged in recent years as one of the most effective methods for tackling the supervised classification task, particularly in the field of computer vision.

 Ranked #1 on Time Series Classification on FordA (mean average precision metric)

Activity Recognition Classification +6

Discriminating Spatial and Temporal Relevance in Deep Taylor Decompositions for Explainable Activity Recognition

jfzhang95/pytorch-video-recognition 5 Aug 2019

However, by exploiting a simple technique that removes motion information, we show that it is not the case that this technique is effective as-is for representing relevance in non-image tasks.

Action Recognition