Papers › Frustratingly Simple Few-Shot Object Detection
Frustratingly Simple Few-Shot Object Detection
Xin Wang, Thomas E. Huang, Trevor Darrell, Joseph E. Gonzalez, Fisher Yu
Detecting rare objects from a few examples is an emerging problem. Prior works show meta-learning is a promising approach. But, fine-tuning techniques have drawn scant attention. We find that fine-tuning only the last layer of existing detectors on rare classes is crucial to the few-shot object detection task. Such a simple approach outperforms the meta-learning methods by roughly 2~20 points on current benchmarks and sometimes even doubles the accuracy of the prior methods. However, the high variance in the few samples often leads to the unreliability of existing benchmarks. We revise the evaluation protocols by sampling multiple groups of training examples to obtain stable comparisons and build new benchmarks based on three datasets: PASCAL VOC, COCO and LVIS. Again, our fine-tuning approach establishes a new state of the art on the revised benchmarks. The code as well as the pretrained models are available at https://github.com/ucbdrive/few-shot-object-detection.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Cross-Domain Few-Shot Object Detection | Artaxor | TFA w/cos | mAP | 14.8 | #12 of 16 | Archive leaderboard | report |
| Cross-Domain Few-Shot Object Detection | DIOR | TFA w/cos | mAP | 20.5 | #10 of 15 | Archive leaderboard | report |
| Cross-Domain Few-Shot Object Detection | UODD | TFA w/cos | mAP | 11.8 | #11 of 16 | Archive leaderboard | report |
| Few-Shot Object Detection | MS-COCO (10-shot) | TFA(w/cos) | AP | 10.0 | #27 of 33 | Archive leaderboard | report |
| Few-Shot Object Detection | MS-COCO (10-shot) | TFA(w/fc) | AP | 10.0 | #28 of 33 | Archive leaderboard | report |
| Few-Shot Object Detection | MS-COCO (30-shot) | TFA w/ cos | AP | 13.7 | #20 of 25 | Archive leaderboard | report |
| Few-Shot Object Detection | MS-COCO (30-shot) | TFA w/ fc | AP | 13.4 | #21 of 25 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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