HOIBlender: Blending Lightweight Detection with Vision-Language Priors for Efficient Human-Object Interaction Detection

arXiv:2609.23431 · cs.CV · Submitted 2026-09-20 · Read on arXiv

cs.CV

Submitted: 2026-09-20

Updated: 2026-09-29

Terminology

• Transformer — 21× in this paper · explained in 2 episodes
• Embeddings — 14× in this paper · explained in 2 episodes
• Accuracy — 9× in this paper · explained in 1 episode
• Calibration — 5× in this paper · explained in 7 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Grounding — 3× in this paper · explained in 3 episodes
• Core — 2× in this paper · explained in 2 episodes
• Decoupling — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Affordance — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• BLIP-2-based Vision-Language Advisor — 1× in this paper
• Benchmark — 1× in this paper · explained in 2 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes

Sources

• LW-DETR: A Transformer Replacement to YOLO for Real-Time Detection
• Visual Semantic Role Labeling
• RF-DETR: Neural Architecture Search for Real-Time Detection Transformers

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