Saliency Detection
129 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
Unsupervised Object Localization: Observing the Background to Discover Objects
This way, the salient objects emerge as a by-product without any strong assumption on what an object should be.
Temporal Saliency Detection Towards Explainable Transformer-based Timeseries Forecasting
duongtrung/time-series-temporal-saliency-patterns
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Despite the notable advancements in numerous Transformer-based models, the task of long multi-horizon time series forecasting remains a persistent challenge, especially towards explainability.
PatchRefineNet: Improving Binary Segmentation by Incorporating Signals from Optimal Patch-wise Binarization
Given the logit scores produced by the base segmentation model, each pixel is given a pseudo-label that is obtained by optimally thresholding the logit scores in each image patch.
Panoramic Vision Transformer for Saliency Detection in 360° Videos
hs-yn/paver
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360$^\circ$ video saliency detection is one of the challenging benchmarks for 360$^\circ$ video understanding since non-negligible distortion and discontinuity occur in the projection of any format of 360$^\circ$ videos, and capture-worthy viewpoint in the omnidirectional sphere is ambiguous by nature.
A Weakly Supervised Learning Framework for Salient Object Detection via Hybrid Labels
rmcong/Hybrid-Label-SOD_TCSVT2022
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In this paper, we focus on a new weakly-supervised SOD task under hybrid labels, where the supervision labels include a large number of coarse labels generated by the traditional unsupervised method and a small number of real labels.
Robust RGB-D Fusion for Saliency Detection
zongwei97/rfnet
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In this work, we aim for RGB-D saliency detection that is robust to the low-quality depths which primarily appear in two forms: inaccuracy due to noise and the misalignment to RGB.
ConCL: Concept Contrastive Learning for Dense Prediction Pre-training in Pathology Images
tencentailabhealthcare/concl
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We first benchmark representative SSL methods for dense prediction tasks in pathology images.
A Comprehensive Survey on Video Saliency Detection with Auditory Information: the Audio-visual Consistency Perceptual is the Key!
Video saliency detection (VSD) aims at fast locating the most attractive objects/things/patterns in a given video clip.
Perceptual Quality Assessment of Virtual Reality Videos in the Wild
limuhit/vr-video-quality-in-the-wild
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Investigating how people perceive virtual reality (VR) videos in the wild (i. e., those captured by everyday users) is a crucial and challenging task in VR-related applications due to complex authentic distortions localized in space and time.
Promoting Saliency From Depth: Deep Unsupervised RGB-D Saliency Detection
The laborious and time-consuming manual annotation has become a real bottleneck in various practical scenarios.
