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Found 3 papers, 1 papers with code
Rethinking Lightweight Salient Object Detection via Network Depth-Width Tradeoff
To this end, we design a lightweight framework while maintaining satisfying competitive accuracy.
Pyramid Grafting Network for One-Stage High Resolution Saliency Detection
An attention-based Cross-Model Grafting Module (CMGM) is proposed to enable CNN branch to combine broken detailed information more holistically, guided by different source feature during decoding process.
Ranked #5 on
RGB Salient Object Detection
on UHRSD
(using extra training data)
Receptive Field Broadening and Boosting for Salient Object Detection
Moreover, Unlike multi-path parallel training, MHB randomly selects one branch each time for gradient back propagation in a boosting way.
