Saliency Detection
130 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.
Source: An Unsupervised Game-Theoretic Approach to Saliency Detection
Benchmarks
These leaderboards are used to track progress in Saliency Detection
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Libraries
Use these libraries to find Saliency Detection models and implementations
PASCAL Context
PASCAL-S
DUTS
HKU-IS
DUT-OMRON
iSUN
CAT2000
ECSSD
ReDWeb-S
Lytro Illum
Subtasks
Latest papers with no code
Spectrum-inspired Low-light Image Translation for Saliency Detection
Saliency detection methods are central to several real-world applications such as robot navigation and satellite imagery.
Self-attention in Vision Transformers Performs Perceptual Grouping, Not Attention
To answer this question, we revisited the attention formulation in these models and found that despite the name, computationally, these models perform a special class of relaxation labeling with similarity grouping effects.
HDR image watermarking using saliency detection and quantization index modulation
First, the host image goes through our proposed salient object detection model to produce a saliency map, which is, in turn, exploited to segment the foreground and background of the host image.
HiDAnet: RGB-D Salient Object Detection via Hierarchical Depth Awareness
In this paper, from a new perspective, we propose a novel Hierarchical Depth Awareness network (HiDAnet) for RGB-D saliency detection.
Rethinking Lightweight Salient Object Detection via Network Depth-Width Tradeoff
To this end, we design a lightweight framework while maintaining satisfying competitive accuracy.
Co-Salient Object Detection With Uncertainty-Aware Group Exchange-Masking
To address this issue, this paper presents a group exchange-masking (GEM) strategy for robust CoSOD model learning.
Point Cloud Quality Assessment using 3D Saliency Maps
Considering the importance of saliency detection in quality assessment, we propose an effective full-reference PCQA metric which makes the first attempt to utilize the saliency information to facilitate quality prediction, called point cloud quality assessment using 3D saliency maps (PQSM).
Towards Stable Co-saliency Detection and Object Co-segmentation
In this paper, we present a novel model for simultaneous stable co-saliency detection (CoSOD) and object co-segmentation (CoSEG).
TokenCut: Segmenting Objects in Images and Videos with Self-supervised Transformer and Normalized Cut
This method also achieves competitive results for unsupervised video object segmentation tasks with the DAVIS, SegTV2, and FBMS datasets.
A Unified Two-Stage Group Semantics Propagation and Contrastive Learning Network for Co-Saliency Detection
With the design of negative samples, the noise objects are suppressed.
