Synthesizing diverse human motions in 3d indoor scenes

K Zhao, Y Zhang, S Wang… - Proceedings of the …, 2023 - openaccess.thecvf.com
We present a novel method for populating 3D indoor scenes with virtual humans that can
navigate in the environment and interact with objects in a realistic manner. Existing …

A review on artificial intelligence applications for facades

A Duran, C Waibel, V Piccioni, B Bickel… - Building and …, 2024 - Elsevier
This review applies a transformer-based topic model to reveal trends and relationships in
Artificial Intelligence (AI)-driven facade research, with a focus on architectural …

Radarverses in metaverses: A CPSI-based architecture for 6S radar systems in CPSS

Y Liu, Y Shen, Y Tian, Y Ai, B Tian… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Metaverses have caused significant changes in the industry and their academic foundation
can be traced back to the term cyber–physical–social systems (CPSS), which was proposed …

Parallel radars: from digital twins to digital intelligence for smart radar systems

Y Liu, Y Shen, L Fan, Y Tian, Y Ai, B Tian, Z Liu… - Sensors, 2022 - mdpi.com
Radar is widely employed in many applications, especially in autonomous driving. At
present, radars are only designed as simple data collectors, and they are unable to meet …

Analyzing CARLA's performance for 2D object detection and monocular depth estimation based on deep learning approaches

AN Tabata, A Zimmer, L dos Santos Coelho… - Expert Systems with …, 2023 - Elsevier
Vehicle and pedestrian perception are key for autonomous vehicles, and camera images
are a common part of the sensor suite. This study explored the use of synthetic datasets from …

Pd-flow: A point cloud denoising framework with normalizing flows

A Mao, Z Du, YH Wen, J Xuan, YJ Liu - European Conference on …, 2022 - Springer
Point cloud denoising aims to restore clean point clouds from raw observations corrupted by
noise and outliers while preserving the fine-grained details. We present a novel deep …

[HTML][HTML] Automated production of synthetic point clouds of truss bridges for semantic and instance segmentation using deep learning models

D Lamas, A Justo, M Soilán, B Riveiro - Automation in Construction, 2024 - Elsevier
The cost of obtaining large volumes of bridge data with technologies like laser scanners
hinders the training of deep learning models. To address this, this paper introduces a new …

Real-time multi-modal semantic fusion on unmanned aerial vehicles with label propagation for cross-domain adaptation

S Bultmann, J Quenzel, S Behnke - Robotics and Autonomous Systems, 2023 - Elsevier
Unmanned aerial vehicles (UAVs) equipped with multiple complementary sensors have
tremendous potential for fast autonomous or remote-controlled semantic scene analysis, eg …

Synthehicle: Multi-vehicle multi-camera tracking in virtual cities

F Herzog, J Chen, T Teepe, J Gilg… - Proceedings of the …, 2023 - openaccess.thecvf.com
Smart City applications such as intelligent traffic routing, accident prevention or vehicle
surveillance rely on computer vision methods for exact vehicle localization and tracking …

[HTML][HTML] Deep Learning on 3D Semantic Segmentation: A Detailed Review

T Betsas, A Georgopoulos, A Doulamis… - Remote Sensing, 2025 - mdpi.com
In this paper, an exhaustive review and comprehensive analysis of recent and former deep
learning methods in 3D semantic segmentation (3DSS) is presented. In the related literature …