35 citations · 102 across the 51 of their papers we have counts for
19 papers · 1 filter
SImpHAR: Advancing impedance-based human activity recognition using 3D simulation and text-to-motion models
Lala Shakti Swarup Ray, Mengxi Liu, Deepika Gurung +3
Human Activity Recognition (HAR) with wearable sensors is essential for applications in healthcare, fitness, and human-computer interaction. Bio-impedance sensing offers unique adv…
PIM: Physics-Informed Multi-task Pre-training for Improving Inertial Sensor-Based Human Activity Recognition
Dominique Nshimyimana, Vitor Fortes Rey, Sungho Suh +2
Human activity recognition (HAR) with deep learning models relies on large amounts of labeled data, often challenging to obtain due to associated cost, time, and labor. Self-superv…
OV-HHIR: Open Vocabulary Human Interaction Recognition Using Cross-modal Integration of Large Language Models
Lala Shakti Swarup Ray, Bo Zhou, Sungho Suh +1
Understanding human-to-human interactions, especially in contexts like public security surveillance, is critical for monitoring and maintaining safety. Traditional activity recogni…
RAD: Region-Aware Diffusion Models for Image Inpainting
Sora Kim, Sungho Suh, Minsik Lee
Diffusion models have achieved remarkable success in image generation, with applications broadening across various domains. Inpainting is one such application that can benefit sign…
A Novel Local-Global Feature Fusion Framework for Body-weight Exercise Recognition with Pressure Mapping Sensors
Davinder Pal Singh, Lala Shakti Swarup Ray, Bo Zhou +2
We present a novel local-global feature fusion framework for body-weight exercise recognition with floor-based dynamic pressure maps. One step further from the existing studies usi…
PressureTransferNet: Human Attribute Guided Dynamic Ground Pressure Profile Transfer using 3D simulated Pressure Maps
Lala Shakti Swarup Ray, Vitor Fortes Rey, Bo Zhou +2
We propose PressureTransferNet, a novel method for Human Activity Recognition (HAR) using ground pressure information. Our approach generates body-specific dynamic ground pressure…
Selecting the motion ground truth for loose-fitting wearables: benchmarking optical MoCap methods
Lala Shakti Swarup Ray, Bo Zhou, Sungho Suh +1
To help smart wearable researchers choose the optimal ground truth methods for motion capturing (MoCap) for all types of loose garments, we present a benchmark, DrapeMoCapBench (DM…
Proxy Anchor-based Unsupervised Learning for Continuous Generalized Category Discovery
Hyungmin Kim, Sungho Suh, Daehwan Kim +3
Recent advances in deep learning have significantly improved the performance of various computer vision applications. However, discovering novel categories in an incremental learni…
A Synthetic Benchmarking Pipeline to Compare Camera Calibration Algorithms
Lala Shakti Swarup Ray, Bo Zhou, Lars Krupp +2
Accurate camera calibration is crucial for various computer vision applications. However, measuring calibration accuracy in the real world is challenging due to the lack of dataset…
ClothFit: Cloth-Human-Attribute Guided Virtual Try-On Network Using 3D Simulated Dataset
Yunmin Cho, Lala Shakti Swarup Ray, Kundan Sai Prabhu Thota +2
Online clothing shopping has become increasingly popular, but the high rate of returns due to size and fit issues has remained a major challenge. To address this problem, virtual t…
MeciFace: Mechanomyography and Inertial Fusion-based Glasses for Edge Real-Time Recognition of Facial and Eating Activities
Hymalai Bello, Sungho Suh, Bo Zhou +1
The increasing prevalence of stress-related eating behaviors and their impact on overall health highlights the importance of effective and ubiquitous monitoring systems. In this pa…
A Knowledge Distillation framework for Multi-Organ Segmentation of Medaka Fish in Tomographic Image
Jwalin Bhatt, Yaroslav Zharov, Sungho Suh +3
Morphological atlases are an important tool in organismal studies, and modern high-throughput Computed Tomography (CT) facilities can produce hundreds of full-body high-resolution…
PresSim: An End-to-end Framework for Dynamic Ground Pressure Profile Generation from Monocular Videos Using Physics-based 3D Simulation
Lala Shakti Swarup Ray, Bo Zhou, Sungho Suh +1
Ground pressure exerted by the human body is a valuable source of information for human activity recognition (HAR) in unobtrusive pervasive sensing. While data collection from pres…
AI-KD: Adversarial learning and Implicit regularization for self-Knowledge Distillation
Hyungmin Kim, Sungho Suh, Sunghyun Baek +4
We present a novel adversarial penalized self-knowledge distillation method, named adversarial learning and implicit regularization for self-knowledge distillation (AI-KD), which r…
TASKED: Transformer-based Adversarial learning for human activity recognition using wearable sensors via Self-KnowledgE Distillation
Sungho Suh, Vitor Fortes Rey, Paul Lukowicz
Wearable sensor-based human activity recognition (HAR) has emerged as a principal research area and is utilized in a variety of applications. Recently, deep learning-based methods…
Estimation of 3D Body Shape and Clothing Measurements from Frontal- and Side-view Images
Kundan Sai Prabhu Thota, Sungho Suh, Bo Zhou +1
The estimation of 3D human body shape and clothing measurements is crucial for virtual try-on and size recommendation problems in the fashion industry but has always been a challen…
Discriminative feature generation for classification of imbalanced data
Sungho Suh, Paul Lukowicz, Yong Oh Lee
The data imbalance problem is a frequent bottleneck in the classification performance of neural networks. In this paper, we propose a novel supervised discriminative feature genera…
Two-stage generative adversarial networks for document image binarization with color noise and background removal
Sungho Suh, Jihun Kim, Paul Lukowicz +1
Document image enhancement and binarization methods are often used to improve the accuracy and efficiency of document image analysis tasks such as text recognition. Traditional non…
Fusion of Global-Local Features for Image Quality Inspection of Shipping Label
Sungho Suh, Paul Lukowicz, Yong Oh Lee
The demands of automated shipping address recognition and verification have increased to handle a large number of packages and to save costs associated with misdelivery. A previous…