# Mask Encoding for Single Shot Instance Segmentation Source: [Mask Encoding for Single Shot Instance Segmentation]() Collection index: [llms.txt]() Data updated: 2025-10-25T22:16:13.371Z Authors: Rufeng Zhang, Zhi Tian, Chunhua Shen, Mingyu You, Youliang Yan Published: 2020-03-26T02:51:17.000Z ## Abstract To date, instance segmentation is dominated by twostage methods, as pioneered by Mask R-CNN. In contrast, one-stage alternatives cannot compete with Mask R-CNN in mask AP, mainly due to the difficulty of compactly representing masks, making the design of one-stage methods very challenging. In this work, we propose a simple singleshot instance segmentation framework, termed mask encoding based instance segmentation (MEInst). Instead of predicting the two-dimensional mask directly, MEInst distills it into a compact and fixed-dimensional representation vector, which allows the instance segmentation task to be incorporated into one-stage bounding-box detectors and results in a simple yet efficient instance segmentation framework. The proposed one-stage MEInst achieves 36.4% in mask AP with single-model (ResNeXt-101-FPN backbone) and single-scale testing on the MS-COCO benchmark. We show that the much simpler and flexible one-stage instance segmentation method, can also achieve competitive performance. This framework can be easily adapted for other instance-level recognition tasks. Code is available at: https://git.io/AdelaiDet ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Instance Segmentation on COCO 2017 (test-dev)](): Instance Segmentation; COCO 2017 (test-dev); AP (Overall): 35.3. - [Object Detection on COCO v2017 (test-dev)](): Object Detection; COCO v2017 (test-dev); mAP: 44.5. - [Instance Segmentation on COCO (test-dev)](): Instance Segmentation; COCO (test-dev); APM: 36.1. - [Object Detection on COCO (test-dev)](): Object Detection; COCO (test-dev); mAP: 38.8. ## Original sources and implementation [Original paper]() [PDF]()