activity
20192024
most citedAdvancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence

78 citations · 197 across the 21 of their papers we have counts for

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Showing cs.CVShow all

18 papers · 1 filter

cs.CV2024★ 1 cited

Debiasing Text-to-Image Diffusion Models

Ruifei He, Chuhui Xue, Haoru Tan +4

Learning-based Text-to-Image (TTI) models like Stable Diffusion have revolutionized the way visual content is generated in various domains. However, recent research has shown that…

cs.CV2023★ 2 cited

Dataset Condensation via Generative Model

David Junhao Zhang, Heng Wang, Chuhui Xue +4

Dataset condensation aims to condense a large dataset with a lot of training samples into a small set. Previous methods usually condense the dataset into the pixels format. However…

cs.CV2023

Free-ATM: Exploring Unsupervised Learning on Diffusion-Generated Images with Free Attention Masks

David Junhao Zhang, Mutian Xu, Chuhui Xue +4

Despite the rapid advancement of unsupervised learning in visual representation, it requires training on large-scale datasets that demand costly data collection, and pose additiona…

cs.CV2023

Lowis3D: Language-Driven Open-World Instance-Level 3D Scene Understanding

Runyu Ding, Jihan Yang, Chuhui Xue +3

Open-world instance-level scene understanding aims to locate and recognize unseen object categories that are not present in the annotated dataset. This task is challenging because…

cs.CV2023★ 15 cited

DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editing

Yujun Shi, Chuhui Xue, Jun Hao Liew +5

Accurate and controllable image editing is a challenging task that has attracted significant attention recently. Notably, DragGAN is an interactive point-based image editing framew…

cs.CV2022★ 3 cited

PV3D: A 3D Generative Model for Portrait Video Generation

Zhongcong Xu, Jianfeng Zhang, Jun Hao Liew +4

Recent advances in generative adversarial networks (GANs) have demonstrated the capabilities of generating stunning photo-realistic portrait images. While some prior works have app…

cs.CV2022★ 4 cited

PLA: Language-Driven Open-Vocabulary 3D Scene Understanding

Runyu Ding, Jihan Yang, Chuhui Xue +3

Open-vocabulary scene understanding aims to localize and recognize unseen categories beyond the annotated label space. The recent breakthrough of 2D open-vocabulary perception is l…

cs.CV2022★ 56 cited

Is synthetic data from generative models ready for image recognition?

Ruifei He, Shuyang Sun, Xin Yu +5

Recent text-to-image generation models have shown promising results in generating high-fidelity photo-realistic images. Though the results are astonishing to human eyes, how applic…

cs.CV2022

1st Place Solution to ECCV 2022 Challenge on Out of Vocabulary Scene Text Understanding: End-to-End Recognition of Out of Vocabulary Words

Zhangzi Zhu, Chuhui Xue, Yu Hao +2

Scene text recognition has attracted increasing interest in recent years due to its wide range of applications in multilingual translation, autonomous driving, etc. In this report,…

cs.CV2022

Runner-Up Solution to ECCV 2022 Challenge on Out of Vocabulary Scene Text Understanding: Cropped Word Recognition

Zhangzi Zhu, Yu Hao, Wenqing Zhang +2

This report presents our 2nd place solution to ECCV 2022 challenge on Out-of-Vocabulary Scene Text Understanding (OOV-ST) : Cropped Word Recognition. This challenge is held in the…

cs.CV2022

Contextual Text Block Detection towards Scene Text Understanding

Chuhui Xue, Jiaxing Huang, Shijian Lu +2

Most existing scene text detectors focus on detecting characters or words that only capture partial text messages due to missing contextual information. For a better understanding…

cs.CV2022

VMRF: View Matching Neural Radiance Fields

Jiahui Zhang, Fangneng Zhan, Rongliang Wu +5

Neural Radiance Fields (NeRF) have demonstrated very impressive performance in novel view synthesis via implicitly modelling 3D representations from multi-view 2D images. However,…

cs.CV2022★ 11 cited

Few Could Be Better Than All: Feature Sampling and Grouping for Scene Text Detection

Jingqun Tang, Wenqing Zhang, Hongye Liu +4

Recently, transformer-based methods have achieved promising progresses in object detection, as they can eliminate the post-processes like NMS and enrich the deep representations. H…

cs.CV2022

Language Matters: A Weakly Supervised Vision-Language Pre-training Approach for Scene Text Detection and Spotting

Chuhui Xue, Wenqing Zhang, Yu Hao +3

Recently, Vision-Language Pre-training (VLP) techniques have greatly benefited various vision-language tasks by jointly learning visual and textual representations, which intuitive…

cs.CV2021★ 6 cited

SeqFormer: Sequential Transformer for Video Instance Segmentation

Junfeng Wu, Yi Jiang, Song Bai +2

In this work, we present SeqFormer for video instance segmentation. SeqFormer follows the principle of vision transformer that models instance relationships among video frames. Nev…

cs.CV2021★ 2 cited

I2C2W: Image-to-Character-to-Word Transformers for Accurate Scene Text Recognition

Chuhui Xue, Jiaxing Huang, Wenqing Zhang +3

Leveraging the advances of natural language processing, most recent scene text recognizers adopt an encoder-decoder architecture where text images are first converted to representa…

cs.CV2020★ 2 cited

Scene Text Detection with Scribble Lines

Wenqing Zhang, Yang Qiu, Minghui Liao +3

Scene text detection, which is one of the most popular topics in both academia and industry, can achieve remarkable performance with sufficient training data. However, the annotati…

cs.CV2020★ 3 cited

FedOCR: Communication-Efficient Federated Learning for Scene Text Recognition

Wenqing Zhang, Yang Qiu, Song Bai +3

While scene text recognition techniques have been widely used in commercial applications, data privacy has rarely been taken into account by this research community. Most existing…