Salient Object Detection
235 papers with code • 6 benchmarks • 16 datasets
Libraries
Use these libraries to find Salient Object Detection models and implementations
PASCAL-S
DUTS
HKU-IS
DUT-OMRON
ECSSD
SOC
VT5000
HRSOD
EORSSD
Latest papers with no code
Cascaded Interaction with Eroded Deep Supervision for Salient Object Detection
Deep convolutional neural networks have been widely applied in salient object detection and have achieved remarkable results in this field.
SimulFlow: Simultaneously Extracting Feature and Identifying Target for Unsupervised Video Object Segmentation
We evaluate our method on several benchmark datasets and achieve state-of-the-art results.
Unified-modal Salient Object Detection via Adaptive Prompt Learning
Existing single-modal and multi-modal salient object detection (SOD) methods focus on designing specific architectures tailored for their respective tasks.
All in One: RGB, RGB-D, and RGB-T Salient Object Detection
We propose an innovative model framework that provides a unified solution for the salient object detection task of three types of data (RGB, RGB-D, and RGB-T).
Unsupervised and semi-supervised co-salient object detection via segmentation frequency statistics
Our unsupervised model is a great pre-training initialization for our semi-supervised model SS-CoSOD, especially when very limited labeled data is available for training.
VST++: Efficient and Stronger Visual Saliency Transformer
Our previous work, the Visual Saliency Transformer (VST), addressed this constraint from a transformer-based sequence-to-sequence perspective, to unify RGB and RGB-D SOD.
Towards End-to-End Unsupervised Saliency Detection with Self-Supervised Top-Down Context
Unsupervised salient object detection aims to detect salient objects without using supervision signals eliminating the tedious task of manually labeling salient objects.
A Spatial-Temporal Dual-Mode Mixed Flow Network for Panoramic Video Salient Object Detection
First, the ILA module calculates the attention between adjacent level features of consecutive frames of panoramic video to improve the accuracy of extracting salient object features from the spatial flow.
SEMPART: Self-supervised Multi-resolution Partitioning of Image Semantics
Accurately determining salient regions of an image is challenging when labeled data is scarce.
UniST: Towards Unifying Saliency Transformer for Video Saliency Prediction and Detection
While many approaches have crafted task-specific training paradigms for either video saliency prediction or video salient object detection tasks, few attention has been devoted to devising a generalized saliency modeling framework that seamlessly bridges both these distinct tasks.
