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Research map / Detection and segmentation / Open-set and few-shot detection

Learning Transferable Human-Object Interaction Detector With Natural Language Supervision

CVPR 2022 · Detection and segmentation › Open-set and few-shot detection · approach: Human-object interaction detection · 72 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use joint visual-and-text matching with pretrained CLIP featuresTHID · HICO-DET unseenmAP: 13.16 -> 15.53Helped
Add HOI sequence parsing so tokens account for preceding detections (ablation)THID · SWIG-HOI unseenmAP: 6.27 -> 10.04Helped
Add HOI sequence parsing so tokens account for preceding detections (ablation)THID · SWIG-HOI non-raremAP: 12.26 -> 17.67Helped
Replace sequential parsing with SetParser (ablation)THID · SWIG-HOI non-raremAP: 17.67 -> 16.93Hurt
Replace sequential parsing with SetParser (ablation)THID · SWIG-HOI unseenmAP: 10.04 -> 7.07Hurt
Include the pretrained [CLS] token in the sequence parser (ablation)THID · SWIG-HOI unseenmAP: 8.43 -> 10.04Helped
Use learnable prefix and conjunction tokens instead of a fixed interaction sentence template (ablation)THID · SWIG-HOI unseenmAP: 6.96 -> 10.04Helped
Add the text-to-visual classification loss (ablation)THID · SWIG-HOI unseenmAP: 9.30 -> 10.04Helped
Use hold-out cross-entropy loss rather than multi-label soft margin loss (ablation)THID · SWIG-HOI unseenmAP: 6.02 -> 10.04Helped
Append action definitions to the fixed text template (ablation)THID · SWIG-HOI unseenmAP: 6.96 -> 8.22Helped
Append object definitions to the fixed text template (ablation)THID · SWIG-HOI unseenmAP: 6.96 -> 7.70Helped

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