Single Stage Class Agnostic Common Object Detection: A Simple Baseline

TL;DR

This paper introduces SSCOD, a simple, single-stage, class-agnostic common object detection method that effectively detects similar objects across images, including unknown categories, outperforming standard detectors.

Contribution

It presents a novel single-stage framework with an embedded feature branch for class-agnostic common object detection, enhancing performance over baseline methods.

Findings

Significantly outperforms standard object detection baselines.

Effective in detecting both known and unknown object categories.

Built upon and extends the ATSSNet architecture.

Abstract

This paper addresses the problem of common object detection, which aims to detect objects of similar categories from a set of images. Although it shares some similarities with the standard object detection and co-segmentation, common object detection, recently promoted by \cite{Jiang2019a}, has some unique advantages and challenges. First, it is designed to work on both closed-set and open-set conditions, a.k.a. known and unknown objects. Second, it must be able to match objects of the same category but not restricted to the same instance, texture, or posture. Third, it can distinguish multiple objects. In this work, we introduce the Single Stage Common Object Detection (SSCOD) to detect class-agnostic common objects from an image set. The proposed method is built upon the standard single-stage object detector. Furthermore, an embedded branch is introduced to generate the object's representation feature, and their similarity is measured by cosine distance. Experiments are conducted on PASCAL VOC 2007 and COCO 2014 datasets. While being simple and flexible, our proposed SSCOD built upon ATSSNet performs significantly better than the baseline of the standard object detection, while still be able to match objects of unknown categories. Our source code can be found at \href{https://github.com/cybercore-co-ltd/Single-Stage-Common-Object-Detection}{(URL)}