Papers › Meta R-CNN: Towards General Solver for Instance-Level Low-Shot Learning

Meta R-CNN: Towards General Solver for Instance-Level Low-Shot Learning

1 Oct 2019ICCV 2019 10archive 2025-07-28

Xiaopeng Yan, Ziliang Chen, Anni Xu, Xiaoxi Wang, Xiaodan Liang, Liang Lin

Resembling the rapid learning capability of human, low-shot learning empowers vision systems to understand new concepts by training with few samples. Leading approaches derived from meta-learning on images with a single visual object. Obfuscated by a complex background and multiple objects in one image, they are hard to promote the research of low-shot object detection/segmentation. In this work, we present a flexible and general methodology to achieve these tasks. Our work extends Faster /Mask R-CNN by proposing meta-learning over RoI (Region-of-Interest) features instead of a full image feature. This simple spirit disentangles multi-object information merged with the background, without bells and whistles, enabling Faster /Mask R-CNN turn into a meta-learner to achieve the tasks. Specifically, we introduce a Predictor-head Remodeling Network (PRN) that shares its main backbone with Faster /Mask R-CNN. PRN receives images containing low-shot objects with their bounding boxes or masks to infer their class attentive vectors. The vectors take channel-wise soft-attention on RoI features, remodeling those R-CNN predictor heads to detect or segment the objects consistent with the classes these vectors represent. In our experiments, Meta R-CNN yields the new state of the art in low-shot object detection and improves low-shot object segmentation by Mask R-CNN. Code: https://yanxp.github.io/metarcnn.html.

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Code

yanxp/MetaR-CNN pytorch report

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Tasks

Few-Shot Object Detection Meta-Learning Object Object Detection Semantic Segmentation object-detection

Results from the paper archive 2025-07-28

Task	Dataset	Model	Metric	Value	Rank at snapshot	Leaderboard	Report
Few-Shot Object Detection	MS-COCO (10-shot)	Meta R-CNN	AP	8.7	#30 of 33	Archive leaderboard	report

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Methods

Convolution Faster R-CNN Mask R-CNN RPN RoIAlign RoIPool Softmax

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