3 citations · 4 across the 6 of their papers we have counts for
6 papers · 1 filter
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…
The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation
Steffen Wolf, Yuyan Li, Constantin Pape +3
Semantic instance segmentation is the task of simultaneously partitioning an image into distinct segments while associating each pixel with a class label. In commonly used pipeline…
RED-NET: A Recursive Encoder-Decoder Network for Edge Detection
Truc Le, Yuyan Li, Ye Duan
In this paper, we introduce RED-NET: A Recursive Encoder-Decoder Network with Skip-Connections for edge detection in natural images. The proposed network is a novel integration of…