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Deposit, archive and share your final research data in DR-NTU (Data)


Mission: DR-NTU (Data) curates, stores, preserves, makes available and enables the download of digital data generated by the NTU research community. The repository develops and provides guidance for managing, sharing, and reusing research data to promote responsible data sharing in support of open science and research integrity.

Who can deposit? NTU faculty, research staff and students.

What can be deposited? Final research data from projects carried out at NTU. The uploaded content must not infringe upon the copyrights or other intellectual property rights, and must be void of all identifiable information.

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1 to 10 of 2,832 Results
StructLDM: Structured Latent Diffusion for 3D Human Generation
Sep 20, 2024 - S-Lab for Advanced Intelligence
Hu, Tao; Hong, Fangzhou; Liu, Ziwei, 2024, "StructLDM: Structured Latent Diffusion for 3D Human Generation", https://doi.org/10.21979/N9/BXUEXV, DR-NTU (Data), V1
Recent 3D human generative models have achieved remarkable progress by learning 3D-aware GANs from 2D images. However, existing 3D human generative methods model humans in a compact 1D latent space, ignoring the articulated structure and semantics of human body topology. In this...
Candra Adi WIGUNA(Nanyang Technological University)
Sep 19, 2024School of Electrical and Electronic Engineering (EEE)
Appointment: Research Fellow
Performing the City
Sep 17, 2024 - Ella Raidel
Raidel, Ella; Seide, Benjamin; William, Ross, 2024, "Performing the City", https://doi.org/10.21979/N9/9O3M2Q, DR-NTU (Data), V1
This paper explores the use of Cinematic VR as a tool for performative interventions in public spaces within the context of modernist architecture in Singapore. The audio-visual experience interrogates the complex relationship among bodies, memories, and the urban environment. Th...
Data for: Haptic Manipulation of 3D Scans for Geometric Feature Enhancement (Refining 3D scan of a surface by manual haptic exploration)
Sep 16, 2024 - TURLAPATI Sri Harsha
Turlapati, Sri Harsha; Accoto, Dino; Domenico, Campolo, 2024, "Data for: Haptic Manipulation of 3D Scans for Geometric Feature Enhancement (Refining 3D scan of a surface by manual haptic exploration)", https://doi.org/10.21979/N9/S2JEGS, DR-NTU (Data), V1
Object localisation, shape estimation, feature detection are important sub-tasks in overarching applications like industrial tooling, assembly, manufacturing and re-manufacturing which might require robotic automation through manipulation. 3D vision techniques provide robust solu...
Replication Data for: The sand juggernaut: Indonesia’s new capital and the intensification of sand mining in Borneo and Sulawesi
Sep 16, 2024 - Kai Wan YUEN
Yuen, Kai Wan, 2024, "Replication Data for: The sand juggernaut: Indonesia’s new capital and the intensification of sand mining in Borneo and Sulawesi", https://doi.org/10.21979/N9/9ATYSW, DR-NTU (Data), V2, UNF:6:cX6vD0BpbnlORSAIbfYHaA== [fileUNF]
Primary data for The sand juggernaut: Indonesia’s new capital and the intensification of sand mining in Borneo and Sulawesi
FANG Zhou(Nanyang Technological University)
Sep 16, 2024School of Civil and Environmental Engineering (CEE)
Appointment: PhD student
Data and Codes for: Exploring earthquake kinematics and physics using high-frequency seismic waves
Sep 16, 2024 - ZENG Hongyu
Zeng, Hongyu, 2024, "Data and Codes for: Exploring earthquake kinematics and physics using high-frequency seismic waves", https://doi.org/10.21979/N9/5TSPMV, DR-NTU (Data), V1
The material provides necessary codes and data to reproduce results in the theis, Exploring earthquake kinematics and physics using high-frequency seismic waves
ZENG Hongyu(Nanyang Technological University)
Sep 16, 2024Asian School of the Environment (ASE)
Appointment: PhD student
Tracing curves in the plane: geometric-invariant learning from human demonstrations
Tracing curves in the plane: geometric-invariant learning from human demonstrations
Sep 12, 2024 - TURLAPATI Sri Harsha
Turlapati, Sri Harsha, 2024, "Tracing curves in the plane: geometric-invariant learning from human demonstrations", https://doi.org/10.21979/N9/QLAMWF, DR-NTU (Data), V1
The empirical laws governing human-curvilinear movements have been studied using various relationships, including minimum jerk, the 2/3 power law, and the piecewise power law. These laws quantify the speed-curvature relationships of human movements during curve tracing using crit...
TURLAPATI Sri Harsha(Nanyang Technological University)
Sep 12, 2024Robotics Research Centre (RRC)
Appointment: Research Fellow
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