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Cross-Domain Few-Shot Object Detection

The task of Cross-Domain Few-Shot Object Detection (CD-FSOD) aims at tackling FSOD across domains.

Papers

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Showing 1–17 of 17 papers

TitleStatusHype
Detecting Twenty-thousand Classes using Image-level SupervisionCode3
No time to train! Training-Free Reference-Based Instance SegmentationCode3
NTIRE 2025 Challenge on Cross-Domain Few-Shot Object Detection: Methods and ResultsCode2
Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object DetectorCode2
Detect Everything with Few ExamplesCode2
Enhance Then Search: An Augmentation-Search Strategy with Foundation Models for Cross-Domain Few-Shot Object DetectionCode2
Exploring Plain Vision Transformer Backbones for Object DetectionCode2
Frustratingly Simple Few-Shot Object DetectionCode2
DeFRCN: Decoupled Faster R-CNN for Few-Shot Object DetectionCode1
CD-FSOD: A Benchmark for Cross-domain Few-shot Object DetectionCode1
Cross-domain Few-shot Object Detection with Multi-modal Textual EnrichmentCode1
FSCE: Few-Shot Object Detection via Contrastive Proposal EncodingCode1
AcroFOD: An Adaptive Method for Cross-domain Few-shot Object DetectionCode1
CDFormer: Cross-Domain Few-Shot Object Detection Transformer Against Feature ConfusionCode1
Balanced ID-OOD tradeoff transfer makes query based detectors good few shot learners—0
Meta-RCNN: Meta Learning for Few-Shot Object Detection—0
0/1 Deep Neural Networks via Block Coordinate Descent—0
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