SOTAVerified

Human Interaction Recognition

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.

Papers

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Showing 1–22 of 22 papers

TitleStatusHype
Dynamic Scene Understanding from Vision-Language Representations—0
OV-HHIR: Open Vocabulary Human Interaction Recognition Using Cross-modal Integration of Large Language Models—0
CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action RecognitionCode1
Empathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational AgentsCode0
Exploring Vision Transformers for 3D Human Motion-Language Models with Motion Patches—0
SkateFormer: Skeletal-Temporal Transformer for Human Action RecognitionCode2
Learning Mutual Excitation for Hand-to-Hand and Human-to-Human Interaction RecognitionCode0
A Two-stream Hybrid CNN-Transformer Network for Skeleton-based Human Interaction Recognition—0
Interactive Spatiotemporal Token Attention Network for Skeleton-based General Interactive Action RecognitionCode1
Human-to-Human Interaction Detection—0
WiFi-TCN: Temporal Convolution for Human Interaction Recognition based on WiFi signal—0
SkeleTR: Towards Skeleton-based Action Recognition in the Wild—0
Two-person Graph Convolutional Network for Skeleton-based Human Interaction RecognitionCode0
IGFormer: Interaction Graph Transformer for Skeleton-based Human Interaction Recognition—0
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—0
Slow-Fast Auditory Streams For Audio RecognitionCode1
Human Interaction Recognition Framework based on Interacting Body Part Attention—0
Three-Stream Fusion Network for First-Person Interaction Recognition—0
Interaction Relational Network for Mutual Action RecognitionCode0
Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition—0
Deep Convolutional Poses for Human Interaction Recognition in Monocular Videos—0
Facial Descriptors for Human Interaction Recognition In Still Images—0
Show:102550
All datasetsNTU RGB+D 120NTU RGB+DUTBITEPIC-SOUNDSSBUSBU / SBU-RefineUT-Interaction

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SkateFormerAccuracy (Cross-Setup)93.2—Unverified
2CHASE(CTR-GCN)Accuracy (Cross-Setup)92.3—Unverified
3ISTA-NetAccuracy (Cross-Setup)91.7—Unverified
4SkeleTRAccuracy (Cross-Setup)88.3—Unverified
5IGFormerAccuracy (Cross-Setup)86.5—Unverified
6LSTM-IRNAccuracy (Cross-Setup)79.6—Unverified
#ModelMetricClaimedVerifiedStatus
1SkateFormerAccuracy (Cross-Subject)97.1—Unverified
2CHASE(CTR-GCN)Accuracy (Cross-Subject)96.5—Unverified
3SkeleTRAccuracy (Cross-Subject)94.9—Unverified
4IGFormerAccuracy (Cross-Subject)93.6—Unverified
5LSTM-IRN'fc1inter+intraAccuracy (Cross-Subject)90.5—Unverified
#ModelMetricClaimedVerifiedStatus
1H-LSTCMAccuracy98.33—Unverified
2Co-LSTSMAccuracy95—Unverified
3Raptis et al.Accuracy93.3—Unverified
4Donahue et al.Accuracy85—Unverified
#ModelMetricClaimedVerifiedStatus
1H-LSTCMAccuracy94.03—Unverified
2Co-LSTSMAccuracy92.88—Unverified
3Donahue et al.Accuracy80.13—Unverified
#ModelMetricClaimedVerifiedStatus
1Slow-Fast(Finetune by Fivewin team)Top-1 accuracy %55.11—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM-IRN'fc1inter+intraAccuracy98.2—Unverified
#ModelMetricClaimedVerifiedStatus
1IGFormerAccuracy98.4—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM-IRN'fc1inter+intraAccuracy (Set 1)98.3—Unverified