10 citations · 18 across the 7 of their papers we have counts for
6 papers · 1 filter
No-Reference Point Cloud Quality Assessment via Graph Convolutional Network
Wu Chen, Qiuping Jiang, Wei Zhou +3
Three-dimensional (3D) point cloud, as an emerging visual media format, is increasingly favored by consumers as it can provide more realistic visual information than two-dimensiona…
Object Segmentation by Mining Cross-Modal Semantics
Zongwei Wu, Jingjing Wang, Zhuyun Zhou +5
Multi-sensor clues have shown promise for object segmentation, but inherent noise in each sensor, as well as the calibration error in practice, may bias the segmentation accuracy.…
A Weakly Supervised Learning Framework for Salient Object Detection via Hybrid Labels
Runmin Cong, Qi Qin, Chen Zhang +4
Fully-supervised salient object detection (SOD) methods have made great progress, but such methods often rely on a large number of pixel-level annotations, which are time-consuming…
No-Reference Quality Assessment for 360-degree Images by Analysis of Multi-frequency Information and Local-global Naturalness
Wei Zhou, Jiahua Xu, Qiuping Jiang +1
360-degree/omnidirectional images (OIs) have achieved remarkable attentions due to the increasing applications of virtual reality (VR). Compared to conventional 2D images, OIs can…
Progressive Self-Guided Loss for Salient Object Detection
Sheng Yang, Weisi Lin, Guosheng Lin +2
We present a simple yet effective progressive self-guided loss function to facilitate deep learning-based salient object detection (SOD) in images. The saliency maps produced by th…
A Dilated Inception Network for Visual Saliency Prediction
Sheng Yang, Guosheng Lin, Qiuping Jiang +1
Recently, with the advent of deep convolutional neural networks (DCNN), the improvements in visual saliency prediction research are impressive. One possible direction to approach t…