43 citations · 58 across the 5 of their papers we have counts for
5 papers
Salient Object Detection in Traffic Scene through the TSOD10K Dataset
Yu Qiu, Yuhang Sun, Jie Mei +2
Traffic Salient Object Detection (TSOD) aims to segment the objects critical to driving safety by combining semantic (e.g., collision risks) and visual saliency. Unlike SOD in natu…
Boosting Salient Object Detection with Transformer-based Asymmetric Bilateral U-Net
Yu Qiu, Yun Liu, Le Zhang +1
Existing salient object detection (SOD) methods mainly rely on U-shaped convolution neural networks (CNNs) with skip connections to combine the global contexts and local spatial de…
Modal-Adaptive Gated Recoding Network for RGB-D Salient Object Detection
Jinchao Zhu, Xiaoyu Zhang, Xian Fang +2
The multi-modal salient object detection model based on RGB-D information has better robustness in the real world. However, it remains nontrivial to better adaptively balance effec…
MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation
Yu Qiu, Yun Liu, Shijie Li +1
The rapid spread of the new pandemic, i.e., COVID-19, has severely threatened global health. Deep-learning-based computer-aided screening, e.g., COVID-19 infected CT area segmentat…
Salient Object Detection via High-to-Low Hierarchical Context Aggregation
Yun Liu, Yu Qiu, Le Zhang +3
Recent progress on salient object detection mainly aims at exploiting how to effectively integrate convolutional side-output features in convolutional neural networks (CNN). Based…