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Yongjun Yu

2 accepted papers

2026

FSOD-VFM: Few-Shot Object Detection with Vision Foundation Models and Graph Diffusion

ICLR 2026poster

In this paper, we present FSOD-VFM: Few-Shot Object Detectors with Vision Foundation Models, a framework that leverages vision foundation models to tackle the challenge of few-shot object detection. FSOD-VFM integrates three key components: a universal proposal network (UPN) for category-agnostic bo…

Cited by 0SourcecodeScholar
2025

DEIM: DETR with Improved Matching for Fast Convergence

CVPR 2025poster

We introduce DEIM, an innovative and efficient training framework designed to accelerate convergence in real-time object detection with Transformer-based architectures (DETR). To mitigate the sparse supervision inherent in one-to-one (O2O) matching in DETR models, DEIM employs a Dense O2O matching s…