Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks
Nankai University · Inception Institute of Artificial Intelligence · +1 more institution
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
- FWCI
- 42.37
- Percentile
- 100%
- References
- 148
Authors
5Topics & keywords
- Computer science
- Salient
- Artificial intelligence
- RGB color model
- Feature (linguistics)
- Benchmark (surveying)
- Field (mathematics)
- Object (grammar)