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Human Interaction Recognition
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Human Interaction Recognition (HIR) is a field of study that involves the development of computer algorithms to detect and recognize human interactions in videos, images, or other multimedia content. The goal of HIR is to automatically identify and analyze the social interactions between people, their body language, and facial expressions.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Learning Dense Hand Contact Estimation from Imbalanced Data
SkeletonX: Data-Efficient Skeleton-based Action Recognition via Cross-sample Feature Aggregation
Dynamic Scene Understanding from Vision-Language Representations
OV-HHIR: Open Vocabulary Human Interaction Recognition Using Cross-modal Integration of Large Language Models
CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action Recognition
Empathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational Agents
Exploring Vision Transformers for 3D Human Motion-Language Models with Motion Patches
SkateFormer: Skeletal-Temporal Transformer for Human Action Recognition
Learning Mutual Excitation for Hand-to-Hand and Human-to-Human Interaction Recognition
A Two-stream Hybrid CNN-Transformer Network for Skeleton-based Human Interaction Recognition
DECO: Dense Estimation of 3D Human-Scene Contact In The Wild
Interactive Spatiotemporal Token Attention Network for Skeleton-based General Interactive Action Recognition
Human-to-Human Interaction Detection
WiFi-TCN: Temporal Convolution for Human Interaction Recognition based on WiFi signal
Does Vision Accelerate Hierarchical Generalization in Neural Language Learners?
MotionBERT: A Unified Perspective on Learning Human Motion Representations
MGTR: End-to-End Mutual Gaze Detection with Transformer
Two-person Graph Convolutional Network for Skeleton-based Human Interaction Recognition
IGFormer: Interaction Graph Transformer for Skeleton-based Human Interaction Recognition
Capturing and Inferring Dense Full-Body Human-Scene Contact
A Prospective Approach for Human-to-Human Interaction Recognition from Wi-Fi Channel Data using Attention Bidirectional Gated Recurrent Neural Network with GUI Application Implementation
Slow-Fast Auditory Streams For Audio Recognition
One-shot action recognition in challenging therapy scenarios
Human Interaction Recognition Framework based on Interacting Body Part Attention
LAEO-Net++: revisiting people Looking At Each Other in videos
Skeleton-DML: Deep Metric Learning for Skeleton-Based One-Shot Action Recognition
Populating 3D Scenes by Learning Human-Scene Interaction
Boosting Image-based Mutual Gaze Detection using Pseudo 3D Gaze
SL-DML: Signal Level Deep Metric Learning for Multimodal One-Shot Action Recognition
Three-Stream Fusion Network for First-Person Interaction Recognition
Interaction Relational Network for Mutual Action Recognition
LAEO-Net: revisiting people Looking At Each Other in videos
NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding
Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition
Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates
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