Guangming Wang | DeepAI

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112 publications
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Yu Zheng
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∙ 09/10/2023

SC-NeRF: Self-Correcting Neural Radiance Field with Sparse Views

In recent studies, the generalization of neural radiance fields for nove...

0 Liang Song, et al. ∙

∙ 08/10/2023

RLSAC: Reinforcement Learning enhanced Sample Consensus for End-to-End Robust Estimation

Robust estimation is a crucial and still challenging task, which involve...

0 Chang Nie, et al. ∙

∙ 08/08/2023

DELFlow: Dense Efficient Learning of Scene Flow for Large-Scale Point Clouds

Point clouds are naturally sparse, while image pixels are dense. The inc...

0 Chensheng Peng, et al. ∙

∙ 06/20/2023

End-to-end 2D-3D Registration between Image and LiDAR Point Cloud for Vehicle Localization

Robot localization using a previously built map is essential for a varie...

0 Guangming Wang, et al. ∙

∙ 03/22/2023

RegFormer: An Efficient Projection-Aware Transformer Network for Large-Scale Point Cloud Registration

Although point cloud registration has achieved remarkable advances in ob...

0 Jiuming Liu, et al. ∙

∙ 09/27/2022

3D Scene Flow Estimation on Pseudo-LiDAR: Bridging the Gap on Estimating Point Motion

3D scene flow characterizes how the points at the current time flow to t...

0 Chaokang Jiang, et al. ∙

∙ 09/15/2022

FFPA-Net: Efficient Feature Fusion with Projection Awareness for 3D Object Detection

Promising complementarity exists between the texture features of color i...

0 Chaokang Jiang, et al. ∙

∙ 09/11/2022

Unsupervised Learning of 3D Scene Flow with 3D Odometry Assistance

Scene flow represents the 3D motion of each point in the scene, which ex...

0 Guangming Wang, et al. ∙

∙ 09/04/2022

Pseudo-LiDAR for Visual Odometry

In the existing methods, LiDAR odometry shows superior performance, but ...

1 Huiying Deng, et al. ∙

∙ 07/19/2022

What Matters for 3D Scene Flow Network

3D scene flow estimation from point clouds is a low-level 3D motion perc...

0 Guangming Wang, et al. ∙

∙ 06/08/2022

Unsupervised Learning of 3D Scene Flow from Monocular Camera

Scene flow represents the motion of points in the 3D space, which is the...

0 Guangming Wang, et al. ∙

∙ 03/30/2022

Interactive Multi-scale Fusion of 2D and 3D Features for Multi-object Tracking

Multiple object tracking (MOT) is a significant task in achieving autono...

0 Guangming Wang, et al. ∙

∙ 03/04/2022

DetFlowTrack: 3D Multi-object Tracking based on Simultaneous Optimization of Object Detection and Scene Flow Estimation

3D Multi-Object Tracking (MOT) is an important part of the unmanned vehi...

0 Yueling Shen, et al. ∙

∙ 12/06/2021

3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video

Depth and ego-motion estimations are essential for the localization and ...

0 Guangming Wang, et al. ∙

∙ 11/03/2021

Efficient 3D Deep LiDAR Odometry

An efficient 3D point cloud learning architecture, named PWCLO-Net, for ...

12 Guangming Wang, et al. ∙

∙ 09/10/2021

Residual 3D Scene Flow Learning with Context-Aware Feature Extraction

Scene flow estimation is the task to predict the point-wise 3D displacem...

0 Guangming Wang, et al. ∙

∙ 07/08/2021

NccFlow: Unsupervised Learning of Optical Flow With Non-occlusion from Geometry

Optical flow estimation is a fundamental problem of computer vision and ...

6 Guangming Wang, et al. ∙

∙ 06/28/2021

Motion Projection Consistency Based 3D Human Pose Estimation with Virtual Bones from Monocular Videos

Real-time 3D human pose estimation is crucial for human-computer interac...

0 Guangming Wang, et al. ∙

∙ 04/01/2021

Unsupervised Learning of Monocular Depth and Ego-Motion Using Multiple Masks

A new unsupervised learning method of depth and ego-motion using multipl...

0 Guangming Wang, et al. ∙

∙ 12/20/2020

Anchor-Based Spatial-Temporal Attention Convolutional Networks for Dynamic 3D Point Cloud Sequences

Recently, learning based methods for the robot perception from the image...

0 Guangming Wang, et al. ∙

∙ 12/02/2020

PWCLO-Net: Deep LiDAR Odometry in 3D Point Clouds Using Hierarchical Embedding Mask Optimization

A novel 3D point cloud learning model for deep LiDAR odometry, named PWC...

1 Guangming Wang, et al. ∙

∙ 11/27/2020

Spherical Interpolated Convolutional Network with Distance-Feature Density for 3D Semantic Segmentation of Point Clouds

The semantic segmentation of point clouds is an important part of the en...

8 Guangming Wang, et al. ∙

∙ 11/24/2020

Achieving Sample-Efficient and Online-Training-Safe Deep Reinforcement Learning with Base Controllers

Application of Deep Reinforcement Learning (DRL) algorithms in real-worl...

0 Minjian Xin, et al. ∙

∙ 10/12/2020

Hierarchical Attention Learning of Scene Flow in 3D Point Clouds

Scene flow represents the 3D motion of every point in the dynamic enviro...

1 Guangming Wang, et al. ∙

∙ 03/02/2020

Unsupervised Learning of Depth, Optical Flow and Pose with Occlusion from 3D Geometry

In autonomous driving, monocular sequences contain lots of information. ...

9 Guangming Wang, et al. ∙

∙ 01/20/2020

Spectral Pyramid Graph Attention Network for Hyperspectral Image Classification

Convolutional neural networks (CNN) have made significant advances in hy...

0 Tinghuai Wang, et al. ∙

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