AI RESEARCH
A Unified Benchmark for HOI Evaluation across Vision-Language Models and HOI-Specific Methods
arXiv CS.CV
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ArXi:2508.18753v3 Announce Type: replace HOI detection has long been dominated by task-specific models, sometimes with early vision-language backbones such as CLIP. With the rise of large generative VLMs, a key question is whether standalone VLMs can perform HOI detection competitively against specialized HOI methods. Existing benchmarks such as HICO-DET require exact label matching under incomplete annotations, so any unmatched prediction is marked wrong. This unfairly penalizes valid outputs, especially from less constrained VLMs, and makes cross-paradigm comparison unreliable.