21 citations · 26 across the 9 of their papers we have counts for
9 papers
Residual Degradation Learning Unfolding Framework with Mixing Priors across Spectral and Spatial for Compressive Spectral Imaging
Yubo Dong, Dahua Gao, Tian Qiu +3
To acquire a snapshot spectral image, coded aperture snapshot spectral imaging (CASSI) is proposed. A core problem of the CASSI system is to recover the reliable and fine underlyin…
Multi-scale Network with Attentional Multi-resolution Fusion for Point Cloud Semantic Segmentation
Yuyan Li, Ye Duan
In this paper, we present a comprehensive point cloud semantic segmentation network that aggregates both local and global multi-scale information. First, we propose an Angle Correl…
OmniFusion: 360 Monocular Depth Estimation via Geometry-Aware Fusion
Yuyan Li, Yuliang Guo, Zhixin Yan +3
A well-known challenge in applying deep-learning methods to omnidirectional images is spherical distortion. In dense regression tasks such as depth estimation, where structural det…
PanoDepth: A Two-Stage Approach for Monocular Omnidirectional Depth Estimation
Yuyan Li, Zhixin Yan, Ye Duan +1
Omnidirectional 3D information is essential for a wide range of applications such as Virtual Reality, Autonomous Driving, Robotics, etc. In this paper, we propose a novel, model-ag…
Fast Point Voxel Convolution Neural Network with Selective Feature Fusion for Point Cloud Semantic Segmentation
Xu Wang, Yuyan Li, Ye Duan
We present a novel lightweight convolutional neural network for point cloud analysis. In contrast to many current CNNs which increase receptive field by downsampling point cloud, o…
SPNet: Multi-Shell Kernel Convolution for Point Cloud Semantic Segmentation
Yuyan Li, Chuanmao Fan, Xu Wang +1
Feature encoding is essential for point cloud analysis. In this paper, we propose a novel point convolution operator named Shell Point Convolution (SPConv) for shape encoding and l…