Search Results for author:
Found 7 papers, 1 papers with code
Underwater Camouflage Object Detection Dataset
We have made a dataset of camouflage object detection mainly for complex seabed scenes, and named it UnderWater RGB&Sonar, or UW-RS for short.
Interactive Context-Aware Network for RGB-T Salient Object Detection
However, most related works are based on RGB images, which lose massive useful information.
Causality Learning With Wasserstein Generative Adversarial Networks
Recently, the problem has been formulated into a continuous optimization framework with an acyclicity constraint to learn Directed Acyclic Graphs (DAGs).
Hyper-Learning for Gradient-Based Batch Size Adaptation
Scheduling the batch size to increase is an effective strategy to control gradient noise when training deep neural networks.
DAG-WGAN: Causal Structure Learning With Wasserstein Generative Adversarial Networks
Recently, the problem has been formulated into a continuous optimization framework with an acyclicity constraint, allowing for the exploration of deep generative models to better capture data sample distributions and support the discovery of Directed Acyclic Graphs (DAGs) that faithfully represent the underlying data distribution.
Modal-Adaptive Gated Recoding Network for RGB-D Salient Object Detection
Then, a modal-adaptive gate unit (MGU) is proposed to suppress the invalid information and transfer the effective modal features to the recoding mixer and the hybrid branch decoder.
Perception-and-Regulation Network for Salient Object Detection
Effective fusion of different types of features is the key to salient object detection.
