4 accepted papers
Detecting camouflaged objects is expected to be a challenging task due to the hard-distinguihsed boundaries of targets. Although existing learning-based methods have concentrated on utilizing boundary information to enhance camouflaged object detection, the absence of boundary difficulty estimation…
Multiple-suction-cup grasp is preferable for picking large and heavy objects in warehouses. Deep learning methods have been widely used to predict grasp point position for single-suction-cup grasp, but few studies have examined grasp pose detection for a gripper with multiple suction cups. This stud…
The existing empirical risk minimization algorithms learn the association between inputs and labels, and face substantial difficulties when apply to different distributions because of various confounders. Causal intervention becomes a solid solution to this issue by analyzing the visual causality, i…
Most object detection methods have achieved impressive performance on several public benchmarks, instead, facing underwater detection tasks, it is challenging to detect marine targets because of the inherent illumination inhomogeneity in underwater images. Moreover, the imbalanced foreground-backgro…