Search
Search Results
-
HDR-Net-Fusion: Real-time 3D dynamic scene reconstruction with a hierarchical deep reinforcement network
Reconstructing dynamic scenes with commodity depth cameras has many applications in computer graphics, computer vision, and robotics. However, due to...
-
Evaluating and Improving RoSELS for Road Surface Extraction from 3D Automotive LiDAR Point Cloud Sequences
Navigable space determination is a difficult problem encountered in robotics and intelligent vehicle technology and it requires integrated solutions...
-
Backup gateways for IoT mesh network using order-k hops Voronoi diagram
Mesh network is a common topology in deploying Edge/Fog computing in IoT due to its robustness, expandability and reliability. In the Mesh topology,...
-
FDA-PointNet++: A Point Cloud Classification Model Based on Fused Downsampling Strategy and Attention Module
In recent years, the use of deep learning models for point cloud classification and segmentation tasks has increasingly become a hot topic in 3D...
-
Next-generation prognosis framework for pediatric spinal deformities using bio-informed deep learning networks
Predicting pediatric spinal deformity (PSD) from X-ray images collected on the patient’s initial visit is a challenging task. This work builds on our...
-
DODA: Data-Oriented Sim-to-Real Domain Adaptation for 3D Semantic Segmentation
Deep learning approaches achieve prominent success in 3D semantic segmentation. However, collecting densely annotated real-world 3D datasets is...
-
Wrinkle synthesis for cloth mesh with hermite radial basis functions
Designing virtual clothing has received much attention recently due to the increasing need for synthesizing realistically dressed digital humans for...
-
RETRACTED ARTICLE: Cerebrum Tumor Segmentation of High Resolution Magnetic Resonance Images Using 2D-Convolutional Network with Skull Strip**
The automatic segmentation of the tumor region from Magnetic Resonance cerebrum imageries is a difficult task in medical image analysis. Numerous...
-
From classical to deep learning: review on cartilage and bone segmentation techniques in knee osteoarthritis research
Knee osteoarthritis is a major diarthrodial joint disorder with profound global socioeconomic impact. Diagnostic imaging using magnetic resonance...
-
Parsing Objects at a Finer Granularity: A Survey
Fine-grained visual parsing, including fine-grained part segmentation and fine-grained object recognition, has attracted considerable critical...
-
Hybrid mesh generation for the thin shell of thin-shell plastic parts for mold flow analysis
Thin-shell plastic parts exist in many products and are frequently manufactured by injection molding. A thin-shell part typically has a thin shell,...
-
3D Modeling
The chapter introduces the concepts of the raw model and informative model; it clarifies the concept of semantic segmentation and defines the digital...
-
Deep Semantic Segmentation of 3D Plant Point Clouds
Plant phenoty** is an essential step in the plant breeding cycle, necessary to ensure food safety for a growing world population. Standard...
-
Network Security Patterns
Organizations typically focus on building applications and data-driven software to harvest the value from thier data. An enterprise segmentation...
-
Irregular object measurement method based on improved adaptive slicing method
Surface shape feature is a very important index for monitoring objects. However, in the existing slicing methods, the volume measurement accuracy of...
-
DCARN: Deep Context Aware Recurrent Neural Network for Semantic Segmentation of Large Scale Unstructured 3D Point Cloud
Semantic segmentation of large unstructured 3D point clouds is important problem for 3D object recognition which in turn is essential to solving more...
-
RegGeoNet: Learning Regular Representations for Large-Scale 3D Point Clouds
Deep learning has proven an effective tool for 3D point cloud processing. Currently, most deep set architectures are developed for sparse inputs...
-
Reconstructing Human Body Mesh from Point Clouds by Adversarial GP Network
We study the problem of reconstructing the template-aligned mesh for human body estimation from unstructured point cloud data. Recently proposed...
-
Topological and geometrical joint learning for 3D graph data
Traditional convolutional neural networks (CNNs) are limited to be directly applied to 3D graph data due to their inherent grid structure. And most...
-
Graph Convolutional Network with Probabilistic Spatial Regression: Application to Craniofacial Landmark Detection from 3D Photogrammetry
Quantitative evaluation of pediatric craniofacial anomalies relies on the accurate identification of anatomical landmarks and structures. While...