Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks

Nankai University · Inception Institute of Artificial Intelligence · +1 more institution

PubMed
Indexed inarxivcrossrefpubmed

Abstract

The use of RGB-D information for salient object detection (SOD) has been extensively explored in recent years. However, relatively few efforts have been put toward modeling SOD in real-world human activity scenes with RGB-D. In this article, we fill the gap by making the following contributions to RGB-D SOD: 1) we carefully collect a new S al i ent P erson (SIP) data set that consists of ~1 K high-resolution images that cover diverse real-world scenes from various viewpoints, poses, occlusions, illuminations, and background s; 2) we conduct a large-scale (and, so far, the most comprehensive) benchmark comparing contemporary methods, which has long been missing in the field and can serve as a baseline for…

Citation impact

686
total citations
FWCI
42.37
Percentile
100%
References
148
Citations per year

Authors

5

Topics & keywords

Keywords
  • Computer science
  • Salient
  • Artificial intelligence
  • RGB color model
  • Feature (linguistics)
  • Benchmark (surveying)
  • Field (mathematics)
  • Object (grammar)
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