College of Computing and Data Science (CCDS)

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21 to 30 of 311 Results

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 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...
Unlocking the Power of SAM 2 for Few-Shot Segmentation May 22, 2025 - S-Lab for Advanced Intelligence Xu, Qianxiong; Zhu, Lanyun; Liu, Xuanyi; Lin, Guosheng; Long, Cheng; Li, Ziyue; Zhao, Rui, 2025, "Unlocking the Power of SAM 2 for Few-Shot Segmentation", https://doi.org/10.21979/N9/XIDXVT, DR-NTU (Data), V1 Few-Shot Segmentation (FSS) aims to learn class-agnostic segmentation on few classes to segment arbitrary classes, but at the risk of overfitting. To address this, some methods use the well-learned knowledge of foundation models (e.g., SAM) to simplify the learning process. Recen...
Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation May 16, 2025 - S-Lab for Advanced Intelligence Liu, Chenxi; Miao, Hao; Xu, Qianxiong; Zhou, Shaowen; Long, Cheng; Zhao, Yan; Li, Ziyue, 2025, "Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation", https://doi.org/10.21979/N9/6WWC6K, DR-NTU (Data), V1 Multivariate time series forecasting (MTSF) endeavors to predict future observations given historical data, playing a crucial role in time series data management systems. With advancements in large language models (LLMs), recent studies employ textual prompt tuning to infuse the...

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

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...

Unlocking the Power of SAM 2 for Few-Shot Segmentation

May 22, 2025 - S-Lab for Advanced Intelligence

Xu, Qianxiong; Zhu, Lanyun; Liu, Xuanyi; Lin, Guosheng; Long, Cheng; Li, Ziyue; Zhao, Rui, 2025, "Unlocking the Power of SAM 2 for Few-Shot Segmentation", https://doi.org/10.21979/N9/XIDXVT, DR-NTU (Data), V1

Few-Shot Segmentation (FSS) aims to learn class-agnostic segmentation on few classes to segment arbitrary classes, but at the risk of overfitting. To address this, some methods use the well-learned knowledge of foundation models (e.g., SAM) to simplify the learning process. Recen...

Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation

May 16, 2025 - S-Lab for Advanced Intelligence

Liu, Chenxi; Miao, Hao; Xu, Qianxiong; Zhou, Shaowen; Long, Cheng; Zhao, Yan; Li, Ziyue, 2025, "Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation", https://doi.org/10.21979/N9/6WWC6K, DR-NTU (Data), V1

Multivariate time series forecasting (MTSF) endeavors to predict future observations given historical data, playing a crucial role in time series data management systems. With advancements in large language models (LLMs), recent studies employ textual prompt tuning to infuse the...

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