26 citations · 91 across the 39 of their papers we have counts for
14 papers · 1 filter
Explicit Relational Reasoning Network for Scene Text Detection
Yuchen Su, Zhineng Chen, Yongkun Du +4
Connected component (CC) is a proper text shape representation that aligns with human reading intuition. However, CC-based text detection methods have recently faced a developmenta…
TextSSR: Diffusion-based Data Synthesis for Scene Text Recognition
Xingsong Ye, Yongkun Du, Yunbo Tao +1
Scene text recognition (STR) suffers from challenges of either less realistic synthetic training data or the difficulty of collecting sufficient high-quality real-world data, limit…
SVTRv2: CTC Beats Encoder-Decoder Models in Scene Text Recognition
Yongkun Du, Zhineng Chen, Hongtao Xie +2
Connectionist temporal classification (CTC)-based scene text recognition (STR) methods, e.g., SVTR, are widely employed in OCR applications, mainly due to their simple architecture…
Improving Text-guided Object Inpainting with Semantic Pre-inpainting
Yifu Chen, Jingwen Chen, Yingwei Pan +4
Recent years have witnessed the success of large text-to-image diffusion models and their remarkable potential to generate high-quality images. The further pursuit of enhancing the…
DreamMesh: Jointly Manipulating and Texturing Triangle Meshes for Text-to-3D Generation
Haibo Yang, Yang Chen, Yingwei Pan +5
Learning radiance fields (NeRF) with powerful 2D diffusion models has garnered popularity for text-to-3D generation. Nevertheless, the implicit 3D representations of NeRF lack expl…
Hi3D: Pursuing High-Resolution Image-to-3D Generation with Video Diffusion Models
Haibo Yang, Yang Chen, Yingwei Pan +4
Despite having tremendous progress in image-to-3D generation, existing methods still struggle to produce multi-view consistent images with high-resolution textures in detail, espec…
FreeEnhance: Tuning-Free Image Enhancement via Content-Consistent Noising-and-Denoising Process
Yang Luo, Yiheng Zhang, Zhaofan Qiu +4
The emergence of text-to-image generation models has led to the recognition that image enhancement, performed as post-processing, would significantly improve the visual quality of…
CWT-Net: Super-resolution of Histopathology Images Using a Cross-scale Wavelet-based Transformer
Feiyang Jia, Zhineng Chen, Ziying Song +2
Super-resolution (SR) aims to enhance the quality of low-resolution images and has been widely applied in medical imaging. We found that the design principles of most existing meth…
Decoder Pre-Training with only Text for Scene Text Recognition
Shuai Zhao, Yongkun Du, Zhineng Chen +1
Scene text recognition (STR) pre-training methods have achieved remarkable progress, primarily relying on synthetic datasets. However, the domain gap between synthetic and real ima…
AdvQDet: Detecting Query-Based Adversarial Attacks with Adversarial Contrastive Prompt Tuning
Xin Wang, Kai Chen, Xingjun Ma +3
Deep neural networks (DNNs) are known to be vulnerable to adversarial attacks even under a black-box setting where the adversary can only query the model. Particularly, query-based…
Out of Length Text Recognition with Sub-String Matching
Yongkun Du, Zhineng Chen, Caiyan Jia +2
Scene Text Recognition (STR) methods have demonstrated robust performance in word-level text recognition. However, in real applications the text image is sometimes long due to dete…
V3Det Challenge 2024 on Vast Vocabulary and Open Vocabulary Object Detection: Methods and Results
Jiaqi Wang, Yuhang Zang, Pan Zhang +31
Detecting objects in real-world scenes is a complex task due to various challenges, including the vast range of object categories, and potential encounters with previously unknown…
Learning to Rank Patches for Unbiased Image Redundancy Reduction
Yang Luo, Zhineng Chen, Peng Zhou +3
Images suffer from heavy spatial redundancy because pixels in neighboring regions are spatially correlated. Existing approaches strive to overcome this limitation by reducing less…
Instruction-Guided Scene Text Recognition
Yongkun Du, Zhineng Chen, Yuchen Su +2
Multi-modal models have shown appealing performance in visual recognition tasks, as free-form text-guided training evokes the ability to understand fine-grained visual content. How…