This dataverse is a collection of the College of Computing and Data Science’s research data.

Featured Dataverses

In order to use this feature you must have at least one published dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

11 to 20 of 303 Results
Replication Data for: Learning Cache Coherence Traffic for NoC Routing Design
Jul 30, 2025 - Guochu XIONG
Xiong, Guochu, 2025, "Replication Data for: Learning Cache Coherence Traffic for NoC Routing Design", https://doi.org/10.21979/N9/J1RNW8, DR-NTU (Data), V1
The dataset includes the source codes and README file for implementing the design presented in the paper 'Learning Cache Coherence Traffic for NoC Routing Design'.
Guochu XIONG(Nanyang Technological University)
Jul 30, 2025
Research topics: • Network-on-Chip • Cache coherence • Machine Learning
Replication Data for: Dual Downsample Vision Transformer for Handwritten Text Recognition (ICDAR2025)
Jun 26, 2025 - Yew Lee TAN
Tan, Yew Lee, 2025, "Replication Data for: Dual Downsample Vision Transformer for Handwritten Text Recognition (ICDAR2025)", https://doi.org/10.21979/N9/DREQKD, DR-NTU (Data), V1
Replication Data for: Dual Downsample Vision Transformer for Handwritten Text Recognition (ICDAR2025) to uncompress: cat lines_recognition_part_* | tar --zstd -xvf -
BAE project data
BAE project data
Jun 26, 2025 - Yew Lee TAN
Tan, Yew Lee, 2025, "BAE project data", https://doi.org/10.21979/N9/AAEFUZ, DR-NTU (Data), V1
BAE project data
Yew Lee TAN(Nanyang Technological University)
Jun 26, 2025
F-LMM: Grounding Frozen Large Multimodal Models
Jun 12, 2025 - S-Lab for Advanced Intelligence
Wu, Size; Jin, Sheng; Zhang, Wenwei; Xu, Lumin; Liu, Wentao; Li, Wei; Loy, Chen Change, 2025, "F-LMM: Grounding Frozen Large Multimodal Models", https://doi.org/10.21979/N9/M0U5AV, DR-NTU (Data), V1
Endowing Large Multimodal Models (LMMs) with visual grounding capability can significantly enhance AIs’ understanding of the visual world and their interaction with humans. However, existing methods typically fine-tune the parameters of LMMs to learn additional segmentation token...
MOWA: Multiple-in-One Image Warping Model
Jun 5, 2025 - S-Lab for Advanced Intelligence
Liao, Kang; Yue, Zongsheng; Wu, Zhonghua; Loy, Chen Change, 2025, "MOWA: Multiple-in-One Image Warping Model", https://doi.org/10.21979/N9/ZPPMT8, DR-NTU (Data), V1
While recent image warping approaches achieved remarkable success on existing benchmarks, they still require training separate models for each specific task and cannot generalize well to different camera models or customized manipulations. To address diverse types of warping in p...
Alias-Free Latent Diffusion Models: Improving Fractional Shift Equivariance of Diffusion Latent Space
Jun 3, 2025 - S-Lab for Advanced Intelligence
Zhou, Yifan; Xiao, Zeqi; Yang, Shuai; Pan, Xingang, 2025, "Alias-Free Latent Diffusion Models: Improving Fractional Shift Equivariance of Diffusion Latent Space", https://doi.org/10.21979/N9/Y6AOQH, DR-NTU (Data), V1
Latent Diffusion Models (LDMs) are known to have an unstable generation process, where even small perturbations or shifts in the input noise can lead to significantly different outputs. This hinders their applicability in applications requiring consistent results. In this work, w...
DoF-Gaussian: Controllable Depth-of-Field for 3D Gaussian Splatting
Jun 3, 2025 - S-Lab for Advanced Intelligence
Shen, Liao; Liu, Tianqi; Sun, Huiqiang; Li, Jiaqi; Cao, Zhiguo; Li, Wei; Loy, Chen Change, 2025, "DoF-Gaussian: Controllable Depth-of-Field for 3D Gaussian Splatting", https://doi.org/10.21979/N9/JKJHNJ, DR-NTU (Data), V1
Recent advances in 3D Gaussian Splatting (3D-GS) have shown remarkable success in representing 3D scenes and generating high-quality, novel views in real-time. However, 3D-GS and its variants assume that input images are captured based on pinhole imaging and are fully in focus. T...
NeuS: Physics and Geometry-Augmented Neural Implicit Surfaces for Rigid Bodies
May 22, 2025 - S-Lab for Advanced Intelligence
Xu, Yuanmu; Hou, Guanli; Hu, Jiangbei; Ren, Tenglong; Wang, Xiaokun; Zhang, Yalan; Ban, Xiaojuan; Qian, Chen; Hou, Fei; He, Ying, 2025, "NeuS: Physics and Geometry-Augmented Neural Implicit Surfaces for Rigid Bodies", https://doi.org/10.21979/N9/LTXKFL, DR-NTU (Data), V1
This paper tackles the challenges of physics-based simulation of rigid bodies in neural rendering, focusing on 3D model representation and collision handling. A synthetic and real-world dataset is also included in the paper.
Add Data

Log in to create a dataverse or add a dataset.

Log In
Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.