Papers Activity Recognition
“Activity Recognition” 태그가 달린 논문 1,380편 · 필터 해제
Foundation models for movement data: Are they ready for prime-time?
Foundation models (FMs) trained on large-scale accelerometer data have been proposed as general-purpose feature extractors for health monitoring, but systematic evidence of their advantages is lacking. We present the fir…
Activity RecognitionAction RecognitionEquipment-centric workpiece localization in near real-time using deep learning-based vision and event-driven finite state machines
Continuous workpiece localization is essential for traceability and process coordination in hot forging, but direct tracking is unreliable because of extreme temperatures, surface degradation, and irregular routing. This…
Activity RecognitionSteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments
Existing video benchmarks evaluate action recognition on consumer videos, egocentric recordings, or simulated industrial environments. They do not test vision-language models under the visual and procedural conditions of…
Activity RecognitionAction RecognitionQFedAgent: Quantum-Enhanced Personalized Federated Learning for Multi-Agent Activity Recognition
Federated learning (FL) enables collaborative model training across distributed devices without sharing raw data, making it suitable for privacy-sensitive robotic sensing applications. However, multi-agent systems genera…
Personalized Federated LearningActivity RecognitionBit-ViP: Leveraging Bit-planes to Preserve Visual Privacy in Images through Obfuscation
The unprecedented growth of computer vision applications, such as surveillance systems and social media, raises security and visual privacy concerns, especially when data is stored on cloud servers. Image obfuscation off…
Activity RecognitionTowards a Bathroom-Centered Human-Building Digital Twin Framework for Indoor Safety Analysis
Bathroom use is a critical safety challenge for older adults because wet surfaces, constrained layouts, limited support, and frequent posture transitions are concentrated within a small domestic space. These conditions c…
Activity RecognitionMemory-Augmented LSTM Autoencoder for Unsupervised Activity Recognition with IMU Sensor Fusion
HAR using Inertial Measurement Unit (IMU) sensors is vital for healthcare monitoring and rehabilitation. Despite deep learning advancements, major challenges remain: reliance on labeled data, multi-sensor fusion complexi…
Activity RecognitionSemantically-Aware Diver Activity Recognition Framework for Effective Underwater Multi-Human-Robot Collaboration
Effective multi-human-robot collaboration is essential for expanding human-led operations in the challenging and high-risk underwater environment. For autonomous underwater vehicles (AUVs) to become true teammates, they …
Activity RecognitionHybrid Robustness Verification for Spatio-Temporal Neural Networks
With AI increasingly deployed in safety-critical systems, providing formal robustness guarantees for the underlying models is essential. Existing verification methods either rely on overly conservative approximations or …
Activity RecognitionAction RecognitionAutonomous DrivingBeyond Motion Primitives: Behavioral Activity Recognition from Head-Mounted IMU
AR smart glasses need continuous behavioral context to offer proactive assistance, yet their most practical always-on sensor, the head-mounted Inertial Measurement Unit (IMU), detects only motion primitives such as walki…
Activity RecognitionTranslating Signals to Languages for sEMG-Based Activity Recognition
Surface electromyography (sEMG) signal-based activity recognition has attracted increasing research attention in recent years. To develop accurate sEMG signal-based activity recognizers, numerous approaches have been pro…
Activity RecognitionAnyMo: Geometry-Aware Setup-Agnostic Modeling of Human Motion in the Wild
As wearable and mobile devices become increasingly embedded in daily life, they offer a practical way to continuously sense human motion in the wild. But inertial signals are highly dependent on the sensing setup, includ…
Cross-Modal RetrievalActivity RecognitionMotion CaptioningSuicide Risk Assessment from AI-powered Video Surveillance: An Interpretable Framework for Prevention in Metro Stations
Understanding and monitoring human behavior in metro stations play an important role in supporting suicide prevention efforts, where early identification of high-risk situations can enable timely intervention. This requi…
Semantic SegmentationActivity RecognitionDywave: Event-Aligned Dynamic Tokenization for Heterogeneous IoT Sensing Signals
Internet of Things (IoT) systems continuously collect heterogeneous sensing signals from ubiquitous sensors to support intelligent applications such as human activity analysis, emotion monitoring, and environmental perce…
Computational EfficiencyActivity RecognitionObject DetectionAccLock: Unlocking Identity with Heartbeat Using In-Ear Accelerometers
The widespread use of earphones has enabled various sensing applications, including activity recognition, health monitoring, and context-aware computing. Among these, earphone-based user authentication has become a key t…
Activity RecognitionBARISTA: A Multi-Task Egocentric Benchmark for Compositional Visual Understanding
Scene understanding is central to general physical intelligence, and video is a primary modality for capturing both state and temporal dynamics of a scene. Yet understanding physical processes remains difficult, as model…
Visual Question AnsweringActivity RecognitionObject LocalizationScene UnderstandingPractical Wi-Fi-based Motion Recognition Under Variable Traffic Patterns
Wi-Fi sensing detects human motions and activities by analysing the channel state information (CSI) derived from Wi-Fi transmissions. However, the impact of variable transmission traffic, which dictates the effective sam…
Activity RecognitionDemographic and Linguistic Bias Evaluation in Omnimodal Language Models
This paper provides a comprehensive evaluation of demographic and linguistic biases in omnimodal language models that process text, images, audio, and video within a single framework. Although these models are being wide…
Language IdentificationActivity RecognitionToward Optimal Sampling Rate Selection and Unbiased Classification for Precise Animal Activity Recognition
With the rapid advancements in deep learning techniques, wearable sensor-aided animal activity recognition (AAR) has demonstrated promising performance, thereby improving livestock management efficiency as well as animal…
Classifier calibrationActivity RecognitionHow Class Ontology and Data Scale Affect Audio Transfer Learning
Transfer learning is a crucial concept within deep learning that allows artificial neural networks to benefit from a large pre-training data basis when confronted with a task of limited data. Despite its ubiquitous use a…
Activity RecognitionTransfer LearningScene Recognition