Re-thinking Co-Salient Object Detection

by   Fan Deng-Ping, et al.

In this paper, we conduct a comprehensive study on the co-salient object detection (CoSOD) problem for images. CoSOD is an emerging and rapidly growing extension of salient object detection (SOD), which aims to detect the co-occurring salient objects in a group of images. However, existing CoSOD datasets often have a serious data bias, assuming that each group of images contains salient objects of similar visual appearances. This bias can lead to the ideal settings and effectiveness of models trained on existing datasets, being impaired in real-life situations, where similarities are usually semantic or conceptual. To tackle this issue, we first introduce a new benchmark, called CoSOD3k in the wild, which requires a large amount of semantic context, making it more challenging than existing CoSOD datasets. Our CoSOD3k consists of 3,316 high-quality, elaborately selected images divided into 160 groups with hierarchical annotations. The images span a wide range of categories, shapes, object sizes, and backgrounds. Second, we integrate the existing SOD techniques to build a unified, trainable CoSOD framework, which is long overdue in this field. Specifically, we propose a novel CoEG-Net that augments our prior model EGNet with a co-attention projection strategy to enable fast common information learning. CoEG-Net fully leverages previous large-scale SOD datasets and significantly improves the model scalability and stability. Third, we comprehensively summarize 34 cutting-edge algorithms, benchmarking 16 of them over three challenging CoSOD datasets (iCoSeg, CoSal2015, and our CoSOD3k), and reporting more detailed (i.e., group-level) performance analysis. Finally, we discuss the challenges and future works of CoSOD. We hope that our study will give a strong boost to growth in the CoSOD community


page 1

page 3

page 8

page 11

page 13

page 14

page 18

page 19


Salient Objects in Clutter: Bringing Salient Object Detection to the Foreground

In this paper, we provide a comprehensive evaluation of salient object d...

Concealed Object Detection

We present the first systematic study on concealed object detection (COD...

Salient Object Detection for Images Taken by People With Vision Impairments

Salient object detection is the task of producing a binary mask for an i...

Salient Objects in Clutter

This paper identifies and addresses a serious design bias of existing sa...

Salient Object Detection: A Benchmark

We extensively compare, qualitatively and quantitatively, 40 state-of-th...

Hierarchical Few-Shot Object Detection: Problem, Benchmark and Method

Few-shot object detection (FSOD) is to detect objects with a few example...

Light Field Salient Object Detection: A Review and Benchmark

Salient object detection (SOD) is a long-standing research topic in comp...

Please sign up or login with your details

Forgot password? Click here to reset