RGB Salient Object Detection
97 papers with code • 13 benchmarks • 17 datasets
RGB Salient object detection is a task-based on a visual attention mechanism, in which algorithms aim to explore objects or regions more attentive than the surrounding areas on the scene or RGB images.
( Image credit: Attentive Feedback Network for Boundary-Aware Salient Object Detection )
Benchmarks
These leaderboards are used to track progress in RGB Salient Object Detection
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Libraries
Use these libraries to find RGB Salient Object Detection models and implementations
PASCAL-S
DUTS
HKU-IS
DUT-OMRON
ISTD
SBU
ECSSD
SOC
VT5000
HRSOD
Latest papers with no code
Masking Salient Object Detection, a Mask Region-based Convolutional Neural Network Analysis for Segmentation of Salient Objects
However, there is no extensive comparison between the two networks in the SOD literature endorsing the effectiveness of Mask-RCNNs over FCN when segmenting salient objects.
Distortion-adaptive Salient Object Detection in 360$^\circ$ Omnidirectional Images
Moreover, benchmarking results of the proposed baseline approach and other methods on 360$^\circ$ SOD dataset show the proposed dataset is very challenging, which also validate the usefulness of the proposed dataset and approach to boost the development of SOD on 360$^\circ$ omnidirectional scenes.
Edge-guided Non-local Fully Convolutional Network for Salient Object Detection
To maintain the clear edge structure of salient objects, we propose a novel Edge-guided Non-local FCN (ENFNet) to perform edge guided feature learning for accurate salient object detection.
OGNet: Salient Object Detection with Output-guided Attention Module
However, most of the existing attention modules used in salient object detection are input with the processed feature map itself, which easily leads to the problem of `blind overconfidence'.
Region Refinement Network for Salient Object Detection
Albeit intensively studied, false prediction and unclear boundaries are still major issues of salient object detection.
Nested Network with Two-Stream Pyramid for Salient Object Detection in Optical Remote Sensing Images
Arising from the various object types and scales, diverse imaging orientations, and cluttered backgrounds in optical remote sensing image (RSI), it is difficult to directly extend the success of salient object detection for nature scene image to the optical RSI.
Salient Object Detection With Pyramid Attention and Salient Edges
The first is the exploitation of an essential pyramid attention structure for salient object detection.
Learning Instance Activation Maps for Weakly Supervised Instance Segmentation
However, learning the full extent of pixel-level instance response in a weakly supervised manner remains unexplored.
An Iterative and Cooperative Top-Down and Bottom-Up Inference Network for Salient Object Detection
The top-down process is used for coarse-to-fine saliency estimation, where high-level saliency is gradually integrated with finer lower-layer features to obtain a fine-grained result.
CapSal: Leveraging Captioning to Boost Semantics for Salient Object Detection
To this end, we propose to leverage captioning as an auxiliary semantic task to boost salient object detection in complex scenarios.
