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Activity Recognition
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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
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
MMKE-Bench: A Multimodal Editing Benchmark for Diverse Visual Knowledge
GeoEdit: Geometric Knowledge Editing for Large Language Models
VDT-Auto: End-to-end Autonomous Driving with VLM-Guided Diffusion Transformers
Learning to Generalize without Bias for Open-Vocabulary Action Recognition
Why Are Web AI Agents More Vulnerable Than Standalone LLMs? A Security Analysis
A Causal Lens for Evaluating Faithfulness Metrics
FinP: Fairness-in-Privacy in Federated Learning by Addressing Disparities in Privacy Risk
GNN-XAR: A Graph Neural Network for Explainable Activity Recognition in Smart Homes
EgoSim: An Egocentric Multi-view Simulator and Real Dataset for Body-worn Cameras during Motion and Activity
Evolution 6.0: Evolving Robotic Capabilities Through Generative Design
Random Projections and Natural Sparsity in Time-Series Classification: A Theoretical Analysis
Trunk-branch Contrastive Network with Multi-view Deformable Aggregation for Multi-view Action Recognition
PMAT: Optimizing Action Generation Order in Multi-Agent Reinforcement Learning
On Neural Inertial Classification Networks for Pedestrian Activity Recognition
SALSA-RL: Stability Analysis in the Latent Space of Actions for Reinforcement Learning
FLEKE: Federated Locate-then-Edit Knowledge Editing
Enhancing Smart Environments with Context-Aware Chatbots using Large Language Models
Edit Once, Update Everywhere: A Simple Framework for Cross-Lingual Knowledge Synchronization in LLMs
Revealing and Mitigating Over-Attention in Knowledge Editing
Online hand gesture recognition using Continual Graph Transformers
CoME: An Unlearning-based Approach to Conflict-free Model Editing
SNN-Driven Multimodal Human Action Recognition via Event Camera and Skeleton Data Fusion
Multi-view Video-Pose Pretraining for Operating Room Surgical Activity Recognition
MomentSeeker: A Task-Oriented Benchmark For Long-Video Moment Retrieval
Activation-wise Propagation: A Universal Strategy to Break Timestep Constraints in Spiking Neural Networks for 3D Data Processing
ConSense: Continually Sensing Human Activity with WiFi via Growing and Picking
DELMAN: Dynamic Defense Against Large Language Model Jailbreaking with Model Editing
Personality Editing for Language Models through Relevant Knowledge Editing
IMLE Policy: Fast and Sample Efficient Visuomotor Policy Learning via Implicit Maximum Likelihood Estimation
Frequency-Aware Masked Autoencoders for Human Activity Recognition using Accelerometers
The Mirage of Model Editing: Revisiting Evaluation in the Wild
K-Edit: Language Model Editing with Contextual Knowledge Awareness
FlowAR: une plateforme uniformisée pour la reconnaissance des activités humaines à partir de capteurs binaires
ESPARGOS: An Ultra Low-Cost, Realtime-Capable Multi-Antenna WiFi Channel Sounder
In-sensor 24 classes HAR under 850 Bytes
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