RT-DETRv4 distills vision foundation models into real-time detectors for free gains
ducha_aiki · x · 2026-09-12
The ECCV 2026 paper "RT-DETRv4" (arXiv 2510.25257) introduces a cost-effective distillation framework to boost lightweight real-time object detectors with Vision Foundation Models (VFMs):
- Motivation: lightweight real-time detectors sacrifice feature representation for speed, capping accuracy and on-device deployment.
- Method: a Deep Semantic Injector (DSI) module integrates VFM high-level representations into the detector's deep layers, while a Gradient-guided Adaptive Modulation (GAM) strategy dynamically tunes semantic-transfer intensity based on gradient norm ratios.
- Results: with zero added deployment or inference overhead, RT-DETRv4 delivers consistent, striking gains across diverse DETR-based models.
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