# Saliency Detection

110 papers with code • 7 benchmarks • 13 datasets

Saliency Detection is a preprocessing step in computer vision which aims at finding salient objects in an image.

## Libraries

Use these libraries to find Saliency Detection models and implementations
2 papers
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2 papers
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# U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection

18 May 2020

In this paper, we design a simple yet powerful deep network architecture, U$^2$-Net, for salient object detection (SOD).

26

# Pyramid Feature Attention Network for Saliency detection

To solve this problem, we propose Pyramid Feature Attention network to focus on effective high-level context features and low-level spatial structural features.

5

# Sanity Checks for Saliency Maps

We find that reliance, solely, on visual assessment can be misleading.

4

# Uncertainty Inspired RGB-D Saliency Detection

7 Sep 2020

Our framework includes two main models: 1) a generator model, which maps the input image and latent variable to stochastic saliency prediction, and 2) an inference model, which gradually updates the latent variable by sampling it from the true or approximate posterior distribution.

4

# P2T: Pyramid Pooling Transformer for Scene Understanding

22 Jun 2021

A popular solution to this problem is to use a single pooling operation to reduce the sequence length.

4

# Real Time Image Saliency for Black Box Classifiers

In this work we develop a fast saliency detection method that can be applied to any differentiable image classifier.

3

# Time-Series Anomaly Detection Service at Microsoft

10 Jun 2019

At Microsoft, we develop a time-series anomaly detection service which helps customers to monitor the time-series continuously and alert for potential incidents on time.

3

# CAGNet: Content-Aware Guidance for Salient Object Detection

29 Nov 2019

Beneficial from Fully Convolutional Neural Networks (FCNs), saliency detection methods have achieved promising results.

3

# Specificity-preserving RGB-D Saliency Detection

To effectively fuse cross-modal features in the shared learning network, we propose a cross-enhanced integration module (CIM) and then propagate the fused feature to the next layer for integrating cross-level information.

3

# Inner and Inter Label Propagation: Salient Object Detection in the Wild

27 May 2015

For most natural images, some boundary superpixels serve as the background labels and the saliency of other superpixels are determined by ranking their similarities to the boundary labels based on an inner propagation scheme.

2