Related papers: Towards Spatial Equilibrium Object Detection

Towards Spatial Equilibrium Object Detection

URL: http://arxiv.org/abs/2301.05957v1
Date: Sat, 14 Jan 2023 17:33:26 GMT
Title: Towards Spatial Equilibrium Object Detection
Authors: Zhaohui Zheng, Yuming Chen, Qibin Hou, Xiang Li, Ming-Ming Cheng
Abstract summary: In this paper, we study the spatial disequilibrium problem of modern object detectors. We propose to quantify this problem by measuring the detection performance over zones. This motivates us to design a more generalized measurement, termed Spatial equilibrium Precision.
Score: 88.9747319572368
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Semantic objects are unevenly distributed over images. In this paper, we study the spatial disequilibrium problem of modern object detectors and propose to quantify this ``spatial bias'' by measuring the detection performance over zones. Our analysis surprisingly shows that the spatial imbalance of objects has a great impact on the detection performance, limiting the robustness of detection applications. This motivates us to design a more generalized measurement, termed Spatial equilibrium Precision (SP), to better characterize the detection performance of object detectors. Furthermore, we also present a spatial equilibrium label assignment (SELA) to alleviate the spatial disequilibrium problem by injecting the prior spatial weight into the optimization process of detectors. Extensive experiments on PASCAL VOC, MS COCO, and 3 application datasets on face mask/fruit/helmet images demonstrate the advantages of our method. Our findings challenge the conventional sense of object detectors and show the indispensability of spatial equilibrium. We hope these discoveries would stimulate the community to rethink how an excellent object detector should be. All the source code, evaluation protocols, and the tutorials are publicly available at https://github.com/Zzh-tju/ZoneEval

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