ResearchTrend.AI
A fully end-to-end deep learning approach for real-time simultaneous 3D reconstruction and material recognition

A fully end-to-end deep learning approach for real-time simultaneous 3D reconstruction and material recognition

Cheng Zhao
Li Sun
Rustam Stolkin
    3DV
ArXiv (abs)PDFHTML

Papers citing "A fully end-to-end deep learning approach for real-time simultaneous 3D reconstruction and material recognition"

13 / 13 papers shown
Title
Self-supervised cross-modality learning for uncertainty-aware object detection and recognition in applications which lack pre-labelled training data
Self-supervised cross-modality learning for uncertainty-aware object detection and recognition in applications which lack pre-labelled training data
Irum Mehboob
Li Sun
Alireza Astegarpanah
Rustam Stolkin
UQCV
78
0
0
05 Nov 2024
Object-Oriented Material Classification and 3D Clustering for Improved Semantic Perception and Mapping in Mobile Robots
Object-Oriented Material Classification and 3D Clustering for Improved Semantic Perception and Mapping in Mobile Robots
Siva Krishna Ravipati
Ehsan Latif
Ramviyas Parasuraman
S. Bhandarkar
118
1
0
08 Jul 2024
A Taxonomy of Semantic Information in Robot-Assisted Disaster Response
A Taxonomy of Semantic Information in Robot-Assisted Disaster Response
Tianshu Ruan
Hao Wang
Rustam Stolkin
Manolis Chiou
63
1
0
30 Sep 2022
A Dense Material Segmentation Dataset for Indoor and Outdoor Scene Parsing
A Dense Material Segmentation Dataset for Indoor and Outdoor Scene Parsing
Paul Upchurch
Ransen Niu
3DV
75
24
0
21 Jul 2022
Teaching Cameras to Feel: Estimating Tactile Physical Properties of Surfaces From Images
Teaching Cameras to Feel: Estimating Tactile Physical Properties of Surfaces From Images
Matthew Purri
Kristin J. Dana
33
16
0
29 Apr 2020
Direct Visual-Inertial Odometry with Semi-Dense Mapping
Direct Visual-Inertial Odometry with Semi-Dense Mapping
Pedro Henrique Martins
Dongkyu Choi
Guanghui Wang
MDE
33
6
0
04 Oct 2019
EPANer Team Description Paper for World Robot Challenge 2020
EPANer Team Description Paper for World Robot Challenge 2020
Zhi Yan
Nathan Crombez
Li Sun
13
0
0
05 Sep 2019
Recurrent-OctoMap: Learning State-based Map Refinement for Long-Term Semantic Mapping with 3D-Lidar Data
Recurrent-OctoMap: Learning State-based Map Refinement for Long-Term Semantic Mapping with 3D-Lidar Data
Li Sun
Zhi Yan
Anestis Zaganidis
Cheng Zhao
T. Duckett
3DPC
119
72
0
02 Jul 2018
Context-Aware Mixed Reality: A Framework for Ubiquitous Interaction
Context-Aware Mixed Reality: A Framework for Ubiquitous Interaction
Long Chen
Wen Tang
N. John
T. Wan
Jiangning Zhang
72
16
0
14 Mar 2018
Learning monocular visual odometry with dense 3D mapping from dense 3D flow
Learning monocular visual odometry with dense 3D mapping from dense 3D flow
Cheng Zhao
Li Sun
Pulak Purkait
T. Duckett
Rustam Stolkin
MDE
67
40
0
06 Mar 2018
Dense RGB-D semantic mapping with Pixel-Voxel neural network
Dense RGB-D semantic mapping with Pixel-Voxel neural network
Cheng Zhao
Li Sun
Pulak Purkait
Rustam Stolkin
3DPC
64
26
0
30 Sep 2017
Semantic Augmented Reality Environment with Material-Aware Physical Interactions
Semantic Augmented Reality Environment with Material-Aware Physical Interactions
Long Chen
Karl Francis
Wen Tang
32
8
0
03 Aug 2017
Weakly-supervised DCNN for RGB-D Object Recognition in Real-World Applications Which Lack Large-scale Annotated Training Data
Weakly-supervised DCNN for RGB-D Object Recognition in Real-World Applications Which Lack Large-scale Annotated Training Data
Li Sun
Cheng Zhao
Rustam Stolkin
71
75
0
19 Mar 2017

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.