6 citations · 12 across the 5 of their papers we have counts for
8 papers · 1 filter
Direction-aware Feature-level Frequency Decomposition for Single Image Deraining
Sen Deng, Yidan Feng, Mingqiang Wei +5
We present a novel direction-aware feature-level frequency decomposition network for single image deraining. Compared with existing solutions, the proposed network has three compel…
RF-Net: An End-to-End Image Matching Network based on Receptive Field
Xuelun Shen, Cheng Wang, Xin Li +5
This paper proposes a new end-to-end trainable matching network based on receptive field, RF-Net, to compute sparse correspondence between images. Building end-to-end trainable mat…
PointNLM: Point Nonlocal-Means for vegetation segmentation based on middle echo point clouds
Jonathan Li, Rongren Wu, Yiping Chen +3
Middle-echo, which covers one or a few corresponding points, is a specific type of 3D point cloud acquired by a multi-echo laser scanner. In this paper, we propose a novel approach…
Fast Regularity-Constrained Plane Reconstruction
Yangbin Lin, Jialian Li, Cheng Wang +3
Man-made environments typically comprise planar structures that exhibit numerous geometric relationships, such as parallelism, coplanarity, and orthogonality. Making full use of th…
LO-Net: Deep Real-time Lidar Odometry
Qing Li, Shaoyang Chen, Cheng Wang +4
We present a novel deep convolutional network pipeline, LO-Net, for real-time lidar odometry estimation. Unlike most existing lidar odometry (LO) estimations that go through indivi…
NeuroTreeNet: A New Method to Explore Horizontal Expansion Network
Shenlong Lou, Yan Luo, Qiancong Fan +4
It is widely recognized that the deeper networks or networks with more feature maps have better performance. Existing studies mainly focus on extending the network depth and increa…