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
Salient Object Detection in RGB-D Videos
kerenfu/rdvs
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Ablation experiments were performed on both pseudo and realistic RGB-D video datasets to demonstrate the advantages of individual modules as well as the necessity of introducing realistic depth.
Towards Open-World Co-Salient Object Detection with Generative Uncertainty-aware Group Selective Exchange-Masking
wuyang98/CoSOD
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To simultaneously consider the uncertainty introduced by irrelevant images and the consensus features of the remaining relevant images in the group, we designed a latent variable generator branch and CoSOD transformer branch.
DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation
We present DFormer, a novel RGB-D pretraining framework to learn transferable representations for RGB-D segmentation tasks.
M$^3$Net: Multilevel, Mixed and Multistage Attention Network for Salient Object Detection
To overcome these, we propose the M$^3$Net, i. e., the Multilevel, Mixed and Multistage attention network for Salient Object Detection (SOD).
Salient Object Detection in Optical Remote Sensing Images Driven by Transformer
mathlee/gelenet
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KTM models the contextual correlation knowledge of two middle-level features of different scales based on the self-attention mechanism, and transfers the knowledge to the raw features to generate more discriminative features.
Zero-Shot Co-salient Object Detection Framework
hkxiao/zs-cosod
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Despite recent advancements in deep learning models, these models still rely on training with well-annotated CoSOD datasets.
Point-aware Interaction and CNN-induced Refinement Network for RGB-D Salient Object Detection
By integrating complementary information from RGB image and depth map, the ability of salient object detection (SOD) for complex and challenging scenes can be improved.
Recurrent Multi-scale Transformer for High-Resolution Salient Object Detection
To address above issues, in this work, we first propose a new HRS10K dataset, which contains 10, 500 high-quality annotated images at 2K-8K resolution.
Distortion-aware Transformer in 360° Salient Object Detection
The first is a Distortion Mapping Module, which guides the model to pre-adapt to distorted features globally.
ComPtr: Towards Diverse Bi-source Dense Prediction Tasks via A Simple yet General Complementary Transformer
Specifically, unlike existing methods that over-specialize in a single task or a subset of tasks, ComPtr starts from the more general concept of bi-source dense prediction.
