Search Results for author: Rui Ma

Found 39 papers, 10 papers with code

OSTAF: A One-Shot Tuning Method for Improved Attribute-Focused T2I Personalization

no code implementations17 Mar 2024 Ye Wang, Zili Yi, Rui Ma

Personalized text-to-image (T2I) models not only produce lifelike and varied visuals but also allow users to tailor the images to fit their personal taste.

Attribute

SemanticHuman-HD: High-Resolution Semantic Disentangled 3D Human Generation

no code implementations15 Mar 2024 Peng Zheng, Tao Liu, Zili Yi, Rui Ma

Notably, SemanticHuman-HD is also the first method to achieve 3D-aware image synthesis at $1024^2$ resolution, benefiting from our proposed 3D-aware super-resolution module.

3D-Aware Image Synthesis Disentanglement +1

TaylorGrid: Towards Fast and High-Quality Implicit Field Learning via Direct Taylor-based Grid Optimization

no code implementations22 Feb 2024 Renyi Mao, Qingshan Xu, Peng Zheng, Ye Wang, Tieru Wu, Rui Ma

In this paper, we aim for both fast and high-quality implicit field learning, and propose TaylorGrid, a novel implicit field representation which can be efficiently computed via direct Taylor expansion optimization on 2D or 3D grids.

Novel View Synthesis

EPSD: Early Pruning with Self-Distillation for Efficient Model Compression

no code implementations31 Jan 2024 Dong Chen, Ning Liu, Yichen Zhu, Zhengping Che, Rui Ma, Fachao Zhang, Xiaofeng Mou, Yi Chang, Jian Tang

Instead of a simple combination of pruning and SD, EPSD enables the pruned network to favor SD by keeping more distillable weights before training to ensure better distillation of the pruned network.

Knowledge Distillation Network Pruning +1

3D-SSGAN: Lifting 2D Semantics for 3D-Aware Compositional Portrait Synthesis

no code implementations8 Jan 2024 Ruiqi Liu, Peng Zheng, Ye Wang, Rui Ma

Conversely, some GAN-based 2D portrait synthesis methods can achieve clear disentanglement of facial regions, but they cannot preserve view consistency due to a lack of 3D modeling abilities.

Disentanglement Image Generation

B-Spine: Learning B-Spline Curve Representation for Robust and Interpretable Spinal Curvature Estimation

no code implementations14 Oct 2023 Hao Wang, Qiang Song, Ruofeng Yin, Rui Ma, Yizhou Yu, Yi Chang

In this paper, we propose B-Spine, a novel deep learning pipeline to learn B-spline curve representation of the spine and estimate the Cobb angles for spinal curvature estimation from low-quality X-ray images.

Image-to-Image Translation

Breaking On-device Training Memory Wall: A Systematic Survey

no code implementations17 Jun 2023 Shitian Li, Chunlin Tian, Kahou Tam, Rui Ma, Li Li

In this systematic survey, we aim to explore the current state-of-the-art techniques for breaking on-device training memory walls, focusing on methods that can enable larger and more complex models to be trained on resource-constrained devices.

Navigate

Self-similarity-based super-resolution of photoacoustic angiography from hand-drawn doodles

1 code implementation2 May 2023 Yuanzheng Ma, Wangting Zhou, Rui Ma, Sihua Yang, Yansong Tang, Xun Guan

To address this challenge, we propose a novel approach that employs a super-resolution PAA method trained with forged PAA images.

Image Generation Super-Resolution +1

Network Algebraization and Port Relationship for Power-Electronic-Dominated Power Systems

no code implementations19 Apr 2023 Rui Ma, Xiaowen Yang, Meng Zhan

With this simplest model, the roles of both nodes and the network become apparent. Simulations verify the proposed model framework in the modified 9-bus system.

MXM-CLR: A Unified Framework for Contrastive Learning of Multifold Cross-Modal Representations

no code implementations20 Mar 2023 Ye Wang, Bowei Jiang, Changqing Zou, Rui Ma

Existing cross-modal contrastive representation learning (XM-CLR) methods such as CLIP are not fully suitable for multifold data as they only consider one positive pair and treat other pairs as negative when computing the contrastive loss.

Contrastive Learning Cross-Modal Retrieval +2

P3DC-Shot: Prior-Driven Discrete Data Calibration for Nearest-Neighbor Few-Shot Classification

1 code implementation2 Jan 2023 Shuangmei Wang, Rui Ma, Tieru Wu, Yang Cao

Inspired by the distribution calibration technique which utilizes the distribution or statistics of the base classes to calibrate the data for few-shot tasks, we propose a novel discrete data calibration operation which is more suitable for NN-based few-shot classification.

Classification Few-Shot Learning

Shape-Aware Fine-Grained Classification of Erythroid Cells

1 code implementation28 Dec 2022 Ye Wang, Rui Ma, Xiaoqing Ma, Honghua Cui, Yubin Xiao, Xuan Wu, You Zhou

BMEC contains 5, 666 images of individual erythroid cells, each of which is extracted from the bone marrow erythroid cell smears and professionally annotated to one of the four types of erythroid cells.

Classification Image Classification

Towards Blind Watermarking: Combining Invertible and Non-invertible Mechanisms

1 code implementation24 Dec 2022 Rui Ma, Mengxi Guo, Yi Hou, Fan Yang, Yuan Li, Huizhu Jia, Xiaodong Xie

The CIN is composed of the invertible part to achieve high imperceptibility and the non-invertible part to strengthen the robustness against strong noise attacks.

Realization Scheme for Visual Cryptography with Computer-generated Holograms

no code implementations10 Dec 2022 Tao Yu, Jinge Ma, Guilin Li, Dongyu Yang, Rui Ma, Yishi Shi

This method can expand the application range of visual cryptography and further increase the security of visual cryptography.

Forgetting to Remember: A Scalable Incremental Learning Framework for Cross-Task Blind Image Quality Assessment

1 code implementation15 Sep 2022 Rui Ma, Qingbo Wu, King Ngi Ngan, Hongliang Li, Fanman Meng, Linfeng Xu

More specifically, we develop a dynamic parameter isolation strategy to sequentially update the task-specific parameter subsets, which are non-overlapped with each other.

Blind Image Quality Assessment Incremental Learning

FD-CAM: Improving Faithfulness and Discriminability of Visual Explanation for CNNs

1 code implementation17 Jun 2022 Hui Li, Zihao Li, Rui Ma, Tieru Wu

In this paper, we propose a novel CAM weighting scheme, named FD-CAM, to improve both the faithfulness and discriminability of the CAM-based CNN visual explanation.

Contemporary Recommendation Systems on Big Data and Their Applications: A Survey

no code implementations31 May 2022 Ziyuan Xia, Anchen Sun, Jingyi Xu, Yuanzhe Peng, Rui Ma, Minghui Cheng

This survey paper conducts a comprehensive analysis of the evolution and contemporary landscape of recommendation systems, which have been extensively incorporated across a myriad of web applications.

Collaborative Filtering Recommendation Systems

FPGA-based AI Smart NICs for Scalable Distributed AI Training Systems

no code implementations22 Apr 2022 Rui Ma, Evangelos Georganas, Alexander Heinecke, Andrew Boutros, Eriko Nurvitadhi

The overhead of these collective communication operations in a distributed AI training system can bottleneck its performance, with more pronounced effects as the number of nodes increases.

Data Compression

ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding

5 code implementations CVPR 2022 Dailan He, Ziming Yang, Weikun Peng, Rui Ma, Hongwei Qin, Yan Wang

Recently, learned image compression techniques have achieved remarkable performance, even surpassing the best manually designed lossy image coders.

Image Compression

Phase-SLAM: Phase Based Simultaneous Localization and Mapping for Mobile Structured Light Illumination Systems

1 code implementation22 Jan 2022 Xi Zheng, Rui Ma, Rui Gao, Qi Hao

In this paper, we propose a phase based Simultaneous Localization and Mapping (Phase-SLAM) framework for fast and accurate SLI sensor pose estimation and 3D object reconstruction.

3D Object Reconstruction 3D Reconstruction +4

SAC-GAN: Structure-Aware Image Composition

1 code implementation13 Dec 2021 Hang Zhou, Rui Ma, Ling-Xiao Zhang, Lin Gao, Ali Mahdavi-Amiri, Hao Zhang

Specifically, our network takes the semantic layout features from the input scene image, features encoded from the edges and silhouette in the input object patch, as well as a latent code as inputs, and generates a 2D spatial affine transform defining the translation and scaling of the object patch.

Image Augmentation Object

A Modular 1D-CNN Architecture for Real-time Digital Pre-distortion

no code implementations18 Nov 2021 Udara De Silva, Toshiaki Koike-Akino, Rui Ma, Ao Yamashita, Hideyuki Nakamizo

This study reports a novel hardware-friendly modular architecture for implementing one dimensional convolutional neural network (1D-CNN) digital predistortion (DPD) technique to linearize RF power amplifier (PA) real-time. The modular nature of our design enables DPD system adaptation for variable resource and timing constraints. Our work also presents a co-simulation architecture to verify the DPD performance with an actual power amplifier hardware-in-the-loop. The experimental results with 100 MHz signals show that the proposed 1D-CNN obtains superior performance compared with other neural network architectures for real-time DPD application.

Spatial-Temporal Residual Aggregation for High Resolution Video Inpainting

no code implementations5 Nov 2021 Vishnu Sanjay Ramiya Srinivasan, Rui Ma, Qiang Tang, Zili Yi, Zhan Xu

Recent learning-based inpainting algorithms have achieved compelling results for completing missing regions after removing undesired objects in videos.

Video Inpainting Vocal Bursts Intensity Prediction

Toward Real-world Image Super-resolution via Hardware-based Adaptive Degradation Models

no code implementations20 Oct 2021 Rui Ma, Johnathan Czernik, Xian Du

Most single image super-resolution (SR) methods are developed on synthetic low-resolution (LR) and high-resolution (HR) image pairs, which are simulated by a predetermined degradation operation, e. g., bicubic downsampling.

Image Super-Resolution

Closed-loop Feedback Registration for Consecutive Images of Moving Flexible Targets

no code implementations20 Oct 2021 Rui Ma, Xian Du

Considering the nature of temporal continuity and consecution of the product images, in this paper, we propose a closed-loop feedback registration algorithm for matching and stitching the deformable printed patterns on a moving flexible substrate.

Image Registration

Fast Wireless Sensor Anomaly Detection based on Data Stream in Edge Computing Enabled Smart Greenhouse

no code implementations28 Jul 2021 Yihong Yang, Sheng Ding, YuWen Liu, Shunmei Meng, Xiaoxiao Chi, Rui Ma, Chao Yan

However, traditional anomaly detection algorithms originally designed for anomaly detection in static data have not properly considered the inherent characteristics of data stream produced by wireless sensor such as infiniteness, correlations and concept drift, which may pose a considerable challenge on anomaly detection based on data stream, and lead to low detection accuracy and efficiency.

Anomaly Detection Decision Making +1

Finding structural hole spanners based on community forest model and diminishing marginal utility in large scale social networks

no code implementations Knowledge-Based Systems, 105916. 2020 Yan Zhang, Hua Xu, Yunfeng Xu, Junhui Deng, Juan Gu, Rui Ma, Jie Lai, Jiangtao Hu, Xiaoshuai Yu, Lei Hou, Lidong Gu, Yanling Wei, Yichao Xiao, Junhao Lu

In this paper, we try to give a more visual and detailed definition of structural hole spanner based on the existing work, and propose a novel algorithm to identify structural hole spanner based on community forest model and diminishing marginal utility.

Community Detection Link Prediction +2

MDSSD: Multi-scale Deconvolutional Single Shot Detector for Small Objects

1 code implementation18 May 2018 Lisha Cui, Rui Ma, Pei Lv, Xiaoheng Jiang, Zhimin Gao, Bing Zhou, Mingliang Xu

The performance of small object detection, however, is still less than satisfactory because of the deficiency of semantic information on shallow feature maps.

Object object-detection +1

Tractable Fully Bayesian Inference via Convex Optimization and Optimal Transport Theory

no code implementations29 Sep 2015 Sanggyun Kim, Diego Mesa, Rui Ma, Todd P. Coleman

We demonstrate with optimal transport theory that when the source distribution can be easily sampled from and the target distribution is log-concave, this can be tractably solved with convex optimization.

Bayesian Inference Sleep Staging

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