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Detecting Any Human-Object Interaction Relationship: Universal HOI Detector with Spatial Prompt Learning on Foundation Models

NeurIPS 2023 · Detection and segmentation › Open-set and few-shot detection · approach: Human-object interaction detection · 10 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add BLIP2 foundation model with HO Prompt-guided Decoder to GEN-VLKT-s (ablation)GEN-VLKT-s · V-COCOAP_role #1: 62.91 -> 65.58Helped
add BLIP2 naively via learnable Q-Former queries (no HOPD) (ablation)GEN-VLKT-s · V-COCOAP_role #1: 62.41 -> 62.91No clear effect
add HOPD spatial prompting (ablation)GEN-VLKT-s + BLIP2 · HICO-DET UV UnseenmAP: 21.57 -> 26.05Helped
add GPT knowledge retrieval descriptive texts (ablation)UniHOI-s · V-COCOAP_role #1: 65.58 -> 66.74Helped
add GPT knowledge retrieval descriptive texts (ablation)UniHOI-s · HICO-DET UV UnseenmAP: 26.05 -> 27.41Helped
use BLIP2 instead of CLIP as foundation model (ablation)UniHOI-s · V-COCOAP_role #1: 62.92 -> 65.58Helped
use larger BLIP-2 (ViT-G OPT6.7B) (ablation)UniHOI-s · V-COCOAP_role #1: 65.58 -> 65.92Helped
use FlanT5-XL LLM variant instead of OPT2.7B (ablation)UniHOI-s · V-COCOAP_role #1: 65.58 -> 65.37No clear effect
replace prior best with UniHOI (BLIP2 + spatial prompts)GEN-VLKT-s · HICO-DET Default FullmAP: 33.75 -> 40.06Helped

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