144 citations · 454 across the 36 of their papers we have counts for
6 papers · 1 filter
Density-Aware Convolutional Networks with Context Encoding for Airborne LiDAR Point Cloud Classification
Xiang Li, Mingyang Wang, Congcong Wen +3
To better address challenging issues of the irregularity and inhomogeneity inherently present in 3D point clouds, researchers have been shifting their focus from the design of hand…
Self-Supervised Learning of Depth and Ego-motion with Differentiable Bundle Adjustment
Yunxiao Shi, Jing Zhu, Yi Fang +2
Learning to predict scene depth and camera motion from RGB inputs only is a challenging task. Most existing learning based methods deal with this task in a supervised manner which…
Structure-Attentioned Memory Network for Monocular Depth Estimation
Jing Zhu, Yunxiao Shi, Mengwei Ren +3
Monocular depth estimation is a challenging task that aims to predict a corresponding depth map from a given single RGB image. Recent deep learning models have been proposed to pre…
Learning Object-specific Distance from a Monocular Image
Jing Zhu, Yi Fang, Husam Abu-Haimed +3
Environment perception, including object detection and distance estimation, is one of the most crucial tasks for autonomous driving. Many attentions have been paid on the object de…
Coherent Point Drift Networks: Unsupervised Learning of Non-Rigid Point Set Registration
Lingjing Wang, Xiang Li, Jianchun Chen +1
Given new pairs of source and target point sets, standard point set registration methods often repeatedly conduct the independent iterative search of desired geometric transformati…
Non-Rigid Point Set Registration Networks
Lingjing Wang, Jianchun Chen, Xiang Li +1
Point set registration is defined as a process to determine the spatial transformation from the source point set to the target one. Existing methods often iteratively search for th…