ZERO: Industry-ready Vision Foundation Model with Multi-modal Prompts

TL;DR

ZERO is an industry-ready vision foundation model that uses multi-modal prompts and training on a proprietary dataset to excel in zero-shot industrial applications, outperforming existing models on various benchmarks.

Contribution

Introduces ZERO, the first vision foundation model designed specifically for zero-shot industrial applications using multi-modal prompts and a proprietary dataset.

Findings

Competitive performance on LVIS-Val benchmark

Outperforms existing models on 37 industrial datasets

Achieved top placements in CVPR 2025 challenges

Abstract

Foundation models have revolutionized AI, yet they struggle with zero-shot deployment in real-world industrial settings due to a lack of high-quality, domain-specific datasets. To bridge this gap, Superb AI introduces ZERO, an industry-ready vision foundation model that leverages multi-modal prompting (textual and visual) for generalization without retraining. Trained on a compact yet representative 0.9 million annotated samples from a proprietary billion-scale industrial dataset, ZERO demonstrates competitive performance on academic benchmarks like LVIS-Val and significantly outperforms existing models across 37 diverse industrial datasets. Furthermore, ZERO achieved 2nd place in the CVPR 2025 Object Instance Detection Challenge and 4th place in the Foundational Few-shot Object Detection Challenge, highlighting its practical deployability and generalizability with minimal adaptation and limited data. To the best of our knowledge, ZERO is the first vision foundation model explicitly built for domain-specific, zero-shot industrial applications.