# RDSNet: A New Deep Architecture for Reciprocal Object Detection and Instance Segmentation Source: [RDSNet: A New Deep Architecture for Reciprocal Object Detection and Instance Segmentation]() Collection index: [llms.txt]() Data updated: 2026-01-04T03:11:52.200Z Authors: Shaoru Wang, Yongchao Gong, Junliang Xing, Lichao Huang, Chang Huang, Weiming Hu Published: 2019-12-11T01:10:33.000Z ## Abstract Object detection and instance segmentation are two fundamental computer vision tasks. They are closely correlated but their relations have not yet been fully explored in most previous work. This paper presents RDSNet, a novel deep architecture for reciprocal object detection and instance segmentation. To reciprocate these two tasks, we design a two-stream structure to learn features on both the object level (i.e., bounding boxes) and the pixel level (i.e., instance masks) jointly. Within this structure, information from the two streams is fused alternately, namely information on the object level introduces the awareness of instance and translation variance to the pixel level, and information on the pixel level refines the localization accuracy of objects on the object level in return. Specifically, a correlation module and a cropping module are proposed to yield instance masks, as well as a mask based boundary refinement module for more accurate bounding boxes. Extensive experimental analyses and comparisons on the COCO dataset demonstrate the effectiveness and efficiency of RDSNet. The source code is available at https://github.com/wangsr126/RDSNet. ## 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 (test-dev)](): Instance Segmentation; COCO (test-dev); APM: 39.5. - [Object Detection on MS COCO (test-dev)](): Object Detection; MS COCO (test-dev); mAP@.5: 58.5. - [Object Detection on COCO v2017 (test-dev)](): Object Detection; COCO v2017 (test-dev); mAP: 38.1. - [Object Detection on COCO (test-dev)](): Object Detection; COCO (test-dev); mAP: 40.3. ## Original sources and implementation [Original paper]() [PDF]() [Implementation]()