Weakly Supervised Multi-Task Representation Learning For Human Activity Analysis Using Wearables

Weakly Supervised Multi-Task Representation Learning for Human Activity Analysis Using Wearables

METIER: A Deep Multi-Task Learning Based Activity and User Recognition Model Using Wearable Sensors

Self-supervised Wearable-based Activity Recognition by Learning to Predict Cross-Dimensional Motion

Multi-Task Self-Supervised Learning

Towards Deep Clustering of Human Activities from Wearables

Learning Models of Human Activities and Interactions using Multi-Modal Wearable Sensors

Microsoft Research

Multiview Tracking Using Weakly Supervised Human Motion Prediction

ComputerVisionFoundation Videos

Real-Time Human Action Recognition Using Pose Estimation on Multiple Persons

Algorithm Planet

SelfHAR: Improving Human Activity Recognition through Self-training with Unlabeled Data

Weakly Supervised Action Learning With RNN Based Fine-To-Coarse Modeling

ComputerVisionFoundation Videos

Same Features, Different Day: Weakly Supervised Feature Learning for Seasonal Invariance

ComputerVisionFoundation Videos

Weakly Supervised Learning of Deep ConvNets Recognition and Detection Matlab Projects

PHDPROJECTS. ORG

MedAI Session 20: Many Faces of Weak Supervision in Medical Representation Learning | Jared Dunnmon

Weakly Supervised Action Localization by Generative Attention Modeling

Microsoft Research

counting animals with computer vision | yolo custom object detection & object tracking

AI Technology for Human Activity Recognition of Workers Using Wearable Devices

German Research Center for Artificial Intelligence

ActivityNet A Large-Scale Video Benchmark for Human Activity Understanding