85 citations · 292 across the 19 of their papers we have counts for
7 papers · 1 filter
Robust Real-Time Monocular Human Pose Estimation with Insole-Based Sensor Fusion
Liang Yu, Tao Zhu, Xiangqing Lu +2
Real-time monocular human pose estimation is an important sensing component for human-centered intelligent systems. While recent camera-based methods have achieved impressive accur…
HGA-Quant: Heterogeneity-Aware Quantization for AutoRegressive Visual Generation Models
Xinmeng Liu, Xianglong Yan, Kaicheng Yang +2
Recently, AutoRegressive Visual Generation (ARVG) models have emerged as a competitive paradigm for high-quality image synthesis. However, their substantial computational and memor…
FLOW: Fusing and Shuffling Global and Local Views for Cross-User Human Activity Recognition with IMUs
Qi Qiu, Tao Zhu, Furong Duan +3
Inertial Measurement Unit (IMU) sensors are widely employed for Human Activity Recognition (HAR) due to their portability, energy efficiency, and growing research interest. However…
HARMamba: Efficient and Lightweight Wearable Sensor Human Activity Recognition Based on Bidirectional Mamba
Shuangjian Li, Tao Zhu, Furong Duan +4
Wearable sensor-based human activity recognition (HAR) is a critical research domain in activity perception. However, achieving high efficiency and long sequence recognition remain…
P2LHAP:Wearable sensor-based human activity recognition, segmentation and forecast through Patch-to-Label Seq2Seq Transformer
Shuangjian Li, Tao Zhu, Mingxing Nie +3
Traditional deep learning methods struggle to simultaneously segment, recognize, and forecast human activities from sensor data. This limits their usefulness in many fields such as…
A Multi-Task Deep Learning Approach for Sensor-based Human Activity Recognition and Segmentation
Furong Duan, Tao Zhu, Jinqiang Wang +3
Sensor-based human activity segmentation and recognition are two important and challenging problems in many real-world applications and they have drawn increasing attention from th…
Negative Selection by Clustering for Contrastive Learning in Human Activity Recognition
Jinqiang Wang, Tao Zhu, Liming Chen +2
Contrastive learning has been applied to Human Activity Recognition (HAR) based on sensor data owing to its ability to achieve performance comparable to supervised learning with a…