Search Results for author: Xiaoming Li

Found 38 papers, 20 papers with code

When StyleGAN Meets Stable Diffusion: a $\mathscr{W}_+$ Adapter for Personalized Image Generation

1 code implementation29 Nov 2023 Xiaoming Li, Xinyu Hou, Chen Change Loy

Text-to-image diffusion models have remarkably excelled in producing diverse, high-quality, and photo-realistic images.

Attribute Disentanglement +1

XRMDN: An Extended Recurrent Mixture Density Network for Short-Term Probabilistic Rider Demand Forecasting with High Volatility

no code implementations15 Oct 2023 Xiaoming Li, Hubert Normandin-Taillon, Chun Wang, Xiao Huang

In the realm of Mobility-on-Demand (MoD) systems, the forecasting of rider demand is a cornerstone for operational decision-making and system optimization.

Decision Making Time Series Forecasting

Tree-GPT: Modular Large Language Model Expert System for Forest Remote Sensing Image Understanding and Interactive Analysis

no code implementations7 Oct 2023 Siqi Du, Shengjun Tang, Weixi Wang, Xiaoming Li, Renzhong Guo

This empowers LLMs with the ability to comprehend images, acquire accurate knowledge, generate code, and perform data analysis in a local environment.

Language Modelling Large Language Model

MetaF2N: Blind Image Super-Resolution by Learning Efficient Model Adaptation from Faces

1 code implementation ICCV 2023 Zhicun Yin, Ming Liu, Xiaoming Li, Hui Yang, Longan Xiao, WangMeng Zuo

To evaluate our proposed MetaF2N, we have collected a real-world low-quality dataset with one or multiple faces in each image, and our MetaF2N achieves superior performance on both synthetic and real-world datasets.

Image Generation Image Super-Resolution +1

Ref-Diff: Zero-shot Referring Image Segmentation with Generative Models

no code implementations31 Aug 2023 Minheng Ni, Yabo Zhang, Kailai Feng, Xiaoming Li, Yiwen Guo, WangMeng Zuo

In this work, we introduce a novel Referring Diffusional segmentor (Ref-Diff) for this task, which leverages the fine-grained multi-modal information from generative models.

Image Segmentation Instance Segmentation +2

VQ-Font: Few-Shot Font Generation with Structure-Aware Enhancement and Quantization

1 code implementation27 Aug 2023 Mingshuai Yao, Yabo Zhang, Xianhui Lin, Xiaoming Li, WangMeng Zuo

In this paper, we propose a VQGAN-based framework (i. e., VQ-Font) to enhance glyph fidelity through token prior refinement and structure-aware enhancement.

Font Generation Quantization

Learning Generative Structure Prior for Blind Text Image Super-resolution

1 code implementation CVPR 2023 Xiaoming Li, WangMeng Zuo, Chen Change Loy

To restrict the generative space of StyleGAN so that it obeys the structure of characters yet remains flexible in handling different font styles, we store the discrete features for each character in a codebook.

Image Super-Resolution

NUWA-LIP: Language-Guided Image Inpainting With Defect-Free VQGAN

no code implementations CVPR 2023 Minheng Ni, Xiaoming Li, WangMeng Zuo

Language-guided image inpainting aims to fill the defective regions of an image under the guidance of text while keeping the non-defective regions unchanged.

Image Inpainting

Learning Dual Memory Dictionaries for Blind Face Restoration

1 code implementation15 Oct 2022 Xiaoming Li, Shiguang Zhang, Shangchen Zhou, Lei Zhang, WangMeng Zuo

Generally, it is a challenging and intractable task to improve the photo-realistic performance of blind restoration and adaptively handle the generic and specific restoration scenarios with a single unified model.

Blind Face Restoration

From Face to Natural Image: Learning Real Degradation for Blind Image Super-Resolution

1 code implementation3 Oct 2022 Xiaoming Li, Chaofeng Chen, Xianhui Lin, WangMeng Zuo, Lei Zhang

Notably, LQ face images, which may have the same degradation process as natural images, can be robustly restored with photo-realistic textures by exploiting their strong structural priors.

Image Generation Image Super-Resolution

Semantic-shape Adaptive Feature Modulation for Semantic Image Synthesis

1 code implementation CVPR 2022 Zhengyao Lv, Xiaoming Li, Zhenxing Niu, Bing Cao, WangMeng Zuo

Obviously, a fine-grained part-level semantic layout will benefit object details generation, and it can be roughly inferred from an object's shape.

Image Generation Object

Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution Priors

2 code implementations26 Feb 2022 Chaofeng Chen, Xinyu Shi, Yipeng Qin, Xiaoming Li, Xiaoguang Han, Tao Yang, Shihui Guo

Unlike image-space methods, our FeMaSR restores HR images by matching distorted LR image {\it features} to their distortion-free HR counterparts in our pretrained HR priors, and decoding the matched features to obtain realistic HR images.

Blind Super-Resolution Generative Adversarial Network +2

Cross-Site Severity Assessment of COVID-19 from CT Images via Domain Adaptation

no code implementations8 Sep 2021 Geng-Xin Xu, Chen Liu, Jun Liu, Zhongxiang Ding, Feng Shi, Man Guo, Wei Zhao, Xiaoming Li, Ying WEI, Yaozong Gao, Chuan-Xian Ren, Dinggang Shen

Particularly, we propose a domain translator and align the heterogeneous data to the estimated class prototypes (i. e., class centers) in a hyper-sphere manifold.

Computed Tomography (CT) Domain Adaptation +1

Learning Semantic Person Image Generation by Region-Adaptive Normalization

1 code implementation CVPR 2021 Zhengyao Lv, Xiaoming Li, Xin Li, Fu Li, Tianwei Lin, Dongliang He, WangMeng Zuo

In the first stage, we predict the target semantic parsing maps to eliminate the difficulties of pose transfer and further benefit the latter translation of per-region appearance style.

Pose Transfer Semantic Parsing +1

Measuring Global Multi-Scale Place Connectivity using Geotagged Social Media Data

1 code implementation8 Feb 2021 Zhenlong Li, Xiao Huang, Xinyue Ye, Yuqin Jiang, Martin Yago, Huan Ning, Michael E. Hodgson, Xiaoming Li

In this study, we introduced a global multi-scale place connectivity index (PCI) based on spatial interactions among places revealed by geotagged tweets as a spatiotemporal-continuous and easy-to-implement measurement.

Social and Information Networks

Progressive Semantic-Aware Style Transformation for Blind Face Restoration

1 code implementation CVPR 2021 Chaofeng Chen, Xiaoming Li, Lingbo Yang, Xianhui Lin, Lei Zhang, Kwan-Yee K. Wong

Compared with previous networks, the proposed PSFR-GAN makes full use of the semantic (parsing maps) and pixel (LQ images) space information from different scales of input pairs.

Blind Face Restoration Face Parsing +2

Blind Face Restoration via Deep Multi-scale Component Dictionaries

1 code implementation ECCV 2020 Xiaoming Li, Chaofeng Chen, Shangchen Zhou, Xianhui Lin, WangMeng Zuo, Lei Zhang

Next, with the degraded input, we match and select the most similar component features from their corresponding dictionaries and transfer the high-quality details to the input via the proposed dictionary feature transfer (DFT) block.

Blind Face Restoration Video Super-Resolution

Face Super-Resolution Guided by 3D Facial Priors

1 code implementation ECCV 2020 Xiaobin Hu, Wenqi Ren, John LaMaster, Xiaochun Cao, Xiaoming Li, Zechao Li, Bjoern Menze, Wei Liu

State-of-the-art face super-resolution methods employ deep convolutional neural networks to learn a mapping between low- and high- resolution facial patterns by exploring local appearance knowledge.

Super-Resolution

A GRU-based Mixture Density Network for Data-Driven Dynamic Stochastic Programming

no code implementations26 Jun 2020 Xiaoming Li, Chun Wang, Xiao Huang, Yimin Nie

To fill the gap, in this work, we propose an innovative data-driven dynamic stochastic programming (DD-DSP) framework for time-series decision-making problem, which involves three components: GRU, Gaussian Mixture Model (GMM) and SP.

Decision Making Time Series +1

Enhanced Blind Face Restoration With Multi-Exemplar Images and Adaptive Spatial Feature Fusion

1 code implementation CVPR 2020 Xiaoming Li, Wenyu Li, Dongwei Ren, Hongzhi Zhang, Meng Wang, Wangmeng Zuo

First, given a degraded observation, we select the optimal guidance based on the weighted affine distance on landmark sets, where the landmark weights are learned to make the guidance image optimized to HQ image reconstruction.

Blind Face Restoration Image Reconstruction

Learning Symmetry Consistent Deep CNNs for Face Completion

1 code implementation19 Dec 2018 Xiaoming Li, Ming Liu, Jieru Zhu, WangMeng Zuo, Meng Wang, Guosheng Hu, Lei Zhang

As for missing pixels on both of half-faces, we present a generative reconstruction subnet together with a perceptual symmetry loss to enforce symmetry consistency of recovered structures.

Face Recognition Facial Inpainting

Identity Preserving Face Completion for Large Ocular Region Occlusion

no code implementations23 Jul 2018 Yajie Zhao, Weikai Chen, Jun Xing, Xiaoming Li, Zach Bessinger, Fuchang Liu, WangMeng Zuo, Ruigang Yang

Different from the state-of-the-art face inpainting methods that have no control over the synthesized content and can only handle frontal face pose, our approach can faithfully recover the missing content under various head poses while preserving the identity.

Facial Inpainting

Learning Warped Guidance for Blind Face Restoration

1 code implementation ECCV 2018 Xiaoming Li, Ming Liu, Yuting Ye, WangMeng Zuo, Liang Lin, Ruigang Yang

For better recovery of fine facial details, we modify the problem setting by taking both the degraded observation and a high-quality guided image of the same identity as input to our guided face restoration network (GFRNet).

Blind Face Restoration

Shift-Net: Image Inpainting via Deep Feature Rearrangement

2 code implementations ECCV 2018 Zhaoyi Yan, Xiaoming Li, Mu Li, WangMeng Zuo, Shiguang Shan

To this end, the encoder feature of the known region is shifted to serve as an estimation of the missing parts.

Image Inpainting

Neural Generative Question Answering

1 code implementation WS 2016 Jun Yin, Xin Jiang, Zhengdong Lu, Lifeng Shang, Hang Li, Xiaoming Li

Empirical study shows the proposed model can effectively deal with the variations of questions and answers, and generate right and natural answers by referring to the facts in the knowledge-base.

Generative Question Answering Text Generation

Cannot find the paper you are looking for? You can Submit a new open access paper.