OPUS: A Simple yet Effective Unified Framework for Open-Vocabulary Detection
Recent unified open-vocabulary detection (OVD) supports heterogeneous prompts, including text queries, visual exemplars, and their combinations, but often rely on increasingly complex designs such as heavy cross-modal fusion, staged training, and iterative annotation pipelines. We revisit whether such complexity is necessary in the era of stronger foundation models. Our finding is that unified OVD can be made substantially simpler with semantic-rich visual representations and scalable grounding supervision. We present OPUS (\textbf{O}pen-vocabulary, \textbf{P}rompt-\textbf{U}nified, \textbf{S}imple), a unified detector supporting text, interactive visual, generic visual, and mixed prompti...
| Authors | Xiaoyan Wei, Zhimin Yao, Ruilin Yang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 31 August 2026 |
| Last updated at source | 31 August 2026 |
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