College of Computing and Data Science (CCDS)

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41 to 50 of 303 Results

Related Data for: Hybrid Near- and Far-Field THz UM-MIMO Channel Estimation: A Sparsifying Matrix Learning-Aided Bayesian Approach Feb 28, 2025 - Yuanjian LI Li, Yuanjian; Madhukumar, A. S., 2025, "Related Data for: Hybrid Near- and Far-Field THz UM-MIMO Channel Estimation: A Sparsifying Matrix Learning-Aided Bayesian Approach", https://doi.org/10.21979/N9/HOX79X, DR-NTU (Data), V1 Python source code associated with the publication titled "Hybrid Near- and Far-Field THz UM-MIMO Channel Estimation: A Sparsifying Matrix Learning-Aided Bayesian Approach". These codes can be used to produce simulation figures in this publication.
Yuanjian LI(Nanyang Technological University) Feb 28, 2025
GaussianAnything: Interactive Point Cloud Latent Diffusion for 3D Generation Feb 5, 2025 - S-Lab for Advanced Intelligence Lan, Yushi; Zhou, Shangchen; Lyu, Zhaoyang; Hong, Fangzhou; Yang, Shuai; Dai, Bo; Pan, Xingang; Loy, Chen Change, 2025, "GaussianAnything: Interactive Point Cloud Latent Diffusion for 3D Generation", https://doi.org/10.21979/N9/ZQ85KI, DR-NTU (Data), V1 While 3D content generation has advanced significantly, existing methods still face challenges with input formats, latent space design, and output representations. This paper introduces a novel 3D generation framework that addresses these challenges, offering scalable, high-quali...
Trajectory attention for fine-grained video motion control Feb 4, 2025 - S-Lab for Advanced Intelligence Xiao, Zeqi; Ouyang, Wenqi; Zhou, Yifan; Yang, Shuai; Yang, Lei; Si, Jianlou; Pan, Xingang, 2025, "Trajectory attention for fine-grained video motion control", https://doi.org/10.21979/N9/II0EM4, DR-NTU (Data), V1 Recent advancements in video generation have been greatly driven by video diffusion models, with camera motion control emerging as a crucial challenge in creating view-customized visual content. This paper introduces trajectory attention, a novel approach that performs attention...
Denoising as Adaptation: Noise-Space Domain Adaptation for Image Restoration Feb 4, 2025 - S-Lab for Advanced Intelligence Liao, Kang; Yue, Zongsheng; Wang, Zhouxia; Loy, Chen Change, 2025, "Denoising as Adaptation: Noise-Space Domain Adaptation for Image Restoration", https://doi.org/10.21979/N9/DMB2QK, DR-NTU (Data), V1 Although learning-based image restoration methods have made significant progress, they still struggle with limited generalization to real-world scenarios due to the substantial domain gap caused by training on synthetic data. Existing methods address this issue by improving data...
Host Pathogen Protein-Protein Interactions(Nanyang Technological University) Feb 3, 2025KWOH Chee Keong
Related Data for: PESI: Paratope-Epitope Set Interaction for SARS-CoV-2 Neutralization Prediction Feb 3, 2025 - Coronavirus Neutralizing Antibodies Rashid, Shamima; Wan, Zhang; Kwoh, Chee Keong; Lin, Zhuoyi; Ng, Shaun Yue Hao; Yin, Rui; Senthilnath, J., 2025, "Related Data for: PESI: Paratope-Epitope Set Interaction for SARS-CoV-2 Neutralization Prediction", https://doi.org/10.21979/N9/IZZKTZ, DR-NTU (Data), V1, UNF:6:XqxFQ/x98XTQs7+Ns8GGJw== [fileUNF] This dataset contains 3 versions of epitope-paratope data and their neutralizing data for the SARS-CoV 2 virus. We pre-processed and annotated antibody-antigen binding data from the Observed Antibody Space (OAS) database to obtain these paratopes and epitopes.
SurMo: Surface-based 4D Motion Modeling for Dynamic Human Rendering (CVPR 2024) Jan 16, 2025 - S-Lab for Advanced Intelligence Hu, Tao; Hong, Fangzhou; Liu, Ziwei, 2025, "SurMo: Surface-based 4D Motion Modeling for Dynamic Human Rendering (CVPR 2024)", https://doi.org/10.21979/N9/JDZOJE, DR-NTU (Data), V1 Dynamic human rendering from video sequences has achieved remarkable progress by formulating the rendering as a mapping from static poses to human images. However, existing methods focus on the human appearance reconstruction of every single frame while the temporal motion relati...
FashionEngine: Interactive 3D Human Generation and Editing via Multimodal Controls Jan 16, 2025 - S-Lab for Advanced Intelligence Hu, Tao; Hong, Fangzhou; Chen, Zhaoxi; Liu, Ziwei, 2025, "FashionEngine: Interactive 3D Human Generation and Editing via Multimodal Controls", https://doi.org/10.21979/N9/WRPWAN, DR-NTU (Data), V1 We present FashionEngine, an interactive 3D human generation and editing system that creates 3D digital humans via user-friendly multimodal controls such as natural languages, visual perceptions, and hand-drawing sketches. FashionEngine automates the 3D human production with thre...
TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment Jan 15, 2025 - S-Lab for Advanced Intelligence Liu, Chenxi; Xu, Qianxiong; Miao, Hao; Yang, Sun; Zhang, Lingzheng; Long, Cheng; Li, Ziyue; Zhao, Rui, 2025, "TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment", https://doi.org/10.21979/N9/V1XDVB, DR-NTU (Data), V1 Multivariate time series forecasting (MTSF) aims to learn temporal dynamics among variables to forecast future time series. Existing statistical and deep learning-based methods suffer from limited learnable parameters and small-scale training data. Recently, large language models...

Related Data for: Hybrid Near- and Far-Field THz UM-MIMO Channel Estimation: A Sparsifying Matrix Learning-Aided Bayesian Approach

Feb 28, 2025 - Yuanjian LI

Li, Yuanjian; Madhukumar, A. S., 2025, "Related Data for: Hybrid Near- and Far-Field THz UM-MIMO Channel Estimation: A Sparsifying Matrix Learning-Aided Bayesian Approach", https://doi.org/10.21979/N9/HOX79X, DR-NTU (Data), V1

Python source code associated with the publication titled "Hybrid Near- and Far-Field THz UM-MIMO Channel Estimation: A Sparsifying Matrix Learning-Aided Bayesian Approach". These codes can be used to produce simulation figures in this publication.

Yuanjian LI(Nanyang Technological University)

Feb 28, 2025

GaussianAnything: Interactive Point Cloud Latent Diffusion for 3D Generation

Feb 5, 2025 - S-Lab for Advanced Intelligence

Lan, Yushi; Zhou, Shangchen; Lyu, Zhaoyang; Hong, Fangzhou; Yang, Shuai; Dai, Bo; Pan, Xingang; Loy, Chen Change, 2025, "GaussianAnything: Interactive Point Cloud Latent Diffusion for 3D Generation", https://doi.org/10.21979/N9/ZQ85KI, DR-NTU (Data), V1

While 3D content generation has advanced significantly, existing methods still face challenges with input formats, latent space design, and output representations. This paper introduces a novel 3D generation framework that addresses these challenges, offering scalable, high-quali...

Trajectory attention for fine-grained video motion control

Feb 4, 2025 - S-Lab for Advanced Intelligence

Xiao, Zeqi; Ouyang, Wenqi; Zhou, Yifan; Yang, Shuai; Yang, Lei; Si, Jianlou; Pan, Xingang, 2025, "Trajectory attention for fine-grained video motion control", https://doi.org/10.21979/N9/II0EM4, DR-NTU (Data), V1

Recent advancements in video generation have been greatly driven by video diffusion models, with camera motion control emerging as a crucial challenge in creating view-customized visual content. This paper introduces trajectory attention, a novel approach that performs attention...

Denoising as Adaptation: Noise-Space Domain Adaptation for Image Restoration

Feb 4, 2025 - S-Lab for Advanced Intelligence

Liao, Kang; Yue, Zongsheng; Wang, Zhouxia; Loy, Chen Change, 2025, "Denoising as Adaptation: Noise-Space Domain Adaptation for Image Restoration", https://doi.org/10.21979/N9/DMB2QK, DR-NTU (Data), V1

Although learning-based image restoration methods have made significant progress, they still struggle with limited generalization to real-world scenarios due to the substantial domain gap caused by training on synthetic data. Existing methods address this issue by improving data...

Host Pathogen Protein-Protein Interactions(Nanyang Technological University)

Feb 3, 2025KWOH Chee Keong

Related Data for: PESI: Paratope-Epitope Set Interaction for SARS-CoV-2 Neutralization Prediction

Feb 3, 2025 - Coronavirus Neutralizing Antibodies

Rashid, Shamima; Wan, Zhang; Kwoh, Chee Keong; Lin, Zhuoyi; Ng, Shaun Yue Hao; Yin, Rui; Senthilnath, J., 2025, "Related Data for: PESI: Paratope-Epitope Set Interaction for SARS-CoV-2 Neutralization Prediction", https://doi.org/10.21979/N9/IZZKTZ, DR-NTU (Data), V1, UNF:6:XqxFQ/x98XTQs7+Ns8GGJw== [fileUNF]

This dataset contains 3 versions of epitope-paratope data and their neutralizing data for the SARS-CoV 2 virus. We pre-processed and annotated antibody-antigen binding data from the Observed Antibody Space (OAS) database to obtain these paratopes and epitopes.

SurMo: Surface-based 4D Motion Modeling for Dynamic Human Rendering (CVPR 2024)

Jan 16, 2025 - S-Lab for Advanced Intelligence

Hu, Tao; Hong, Fangzhou; Liu, Ziwei, 2025, "SurMo: Surface-based 4D Motion Modeling for Dynamic Human Rendering (CVPR 2024)", https://doi.org/10.21979/N9/JDZOJE, DR-NTU (Data), V1

Dynamic human rendering from video sequences has achieved remarkable progress by formulating the rendering as a mapping from static poses to human images. However, existing methods focus on the human appearance reconstruction of every single frame while the temporal motion relati...

FashionEngine: Interactive 3D Human Generation and Editing via Multimodal Controls

Jan 16, 2025 - S-Lab for Advanced Intelligence

Hu, Tao; Hong, Fangzhou; Chen, Zhaoxi; Liu, Ziwei, 2025, "FashionEngine: Interactive 3D Human Generation and Editing via Multimodal Controls", https://doi.org/10.21979/N9/WRPWAN, DR-NTU (Data), V1

We present FashionEngine, an interactive 3D human generation and editing system that creates 3D digital humans via user-friendly multimodal controls such as natural languages, visual perceptions, and hand-drawing sketches. FashionEngine automates the 3D human production with thre...

TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment

Jan 15, 2025 - S-Lab for Advanced Intelligence

Liu, Chenxi; Xu, Qianxiong; Miao, Hao; Yang, Sun; Zhang, Lingzheng; Long, Cheng; Li, Ziyue; Zhao, Rui, 2025, "TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment", https://doi.org/10.21979/N9/V1XDVB, DR-NTU (Data), V1

Multivariate time series forecasting (MTSF) aims to learn temporal dynamics among variables to forecast future time series. Existing statistical and deep learning-based methods suffer from limited learnable parameters and small-scale training data. Recently, large language models...

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