DeFloMat: Detection with Flow Matching for Stable and Efficient Generative Object Localization

• URL: http://arxiv.org/abs/2512.22406v1
• Date: Fri, 26 Dec 2025 23:07:40 GMT
• Title: DeFloMat: Detection with Flow Matching for Stable and Efficient Generative Object Localization
• Authors: Hansang Lee, Chaelin Lee, Nieun Seo, Joon Seok Lim, Helen Hong,
• Abstract summary: DeFloMat is a novel generative object detection framework.<n>It addresses the critical latency bottleneck of diffusion-based detectors.<n>DeFloMat achieves state-of-the-art accuracy ($43.32% text AP_10:50$) in only $3$ inference steps.
• Score: 0.5872014229110213
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We propose DeFloMat (Detection with Flow Matching), a novel generative object detection framework that addresses the critical latency bottleneck of diffusion-based detectors, such as DiffusionDet, by integrating Conditional Flow Matching (CFM). Diffusion models achieve high accuracy by formulating detection as a multi-step stochastic denoising process, but their reliance on numerous sampling steps ($T \gg 60$) makes them impractical for time-sensitive clinical applications like Crohn's Disease detection in Magnetic Resonance Enterography (MRE). DeFloMat replaces this slow stochastic path with a highly direct, deterministic flow field derived from Conditional Optimal Transport (OT) theory, specifically approximating the Rectified Flow. This shift enables fast inference via a simple Ordinary Differential Equation (ODE) solver. We demonstrate the superiority of DeFloMat on a challenging MRE clinical dataset. Crucially, DeFloMat achieves state-of-the-art accuracy ($43.32\% \text{ } AP_{10:50}$) in only $3$ inference steps, which represents a $1.4\times$ performance improvement over DiffusionDet's maximum converged performance ($31.03\% \text{ } AP_{10:50}$ at $4$ steps). Furthermore, our deterministic flow significantly enhances localization characteristics, yielding superior Recall and stability in the few-step regime. DeFloMat resolves the trade-off between generative accuracy and clinical efficiency, setting a new standard for stable and rapid object localization.

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