78 citations · 237 across the 40 of their papers we have counts for
42 papers
Turning a CLIP Model into a Scene Text Spotter
Wenwen Yu, Yuliang Liu, Xingkui Zhu +3
We exploit the potential of the large-scale Contrastive Language-Image Pretraining (CLIP) model to enhance scene text detection and spotting tasks, transforming it into a robust ba…
ESTextSpotter: Towards Better Scene Text Spotting with Explicit Synergy in Transformer
Mingxin Huang, Jiaxin Zhang, Dezhi Peng +5
In recent years, end-to-end scene text spotting approaches are evolving to the Transformer-based framework. While previous studies have shown the crucial importance of the intrinsi…
Visual Information Extraction in the Wild: Practical Dataset and End-to-end Solution
Jianfeng Kuang, Wei Hua, Dingkang Liang +4
Visual information extraction (VIE), which aims to simultaneously perform OCR and information extraction in a unified framework, has drawn increasing attention due to its essential…
Looking and Listening: Audio Guided Text Recognition
Wenwen Yu, Mingyu Liu, Biao Yang +5
Text recognition in the wild is a long-standing problem in computer vision. Driven by end-to-end deep learning, recent studies suggest vision and language processing are effective…
ICDAR 2023 Competition on Structured Text Extraction from Visually-Rich Document Images
Wenwen Yu, Chengquan Zhang, Haoyu Cao +24
Structured text extraction is one of the most valuable and challenging application directions in the field of Document AI. However, the scenarios of past benchmarks are limited, an…
SAM3D: Zero-Shot 3D Object Detection via Segment Anything Model
Dingyuan Zhang, Dingkang Liang, Hongcheng Yang +4
With the development of large language models, many remarkable linguistic systems like ChatGPT have thrived and achieved astonishing success on many tasks, showing the incredible p…
Multi-Modal 3D Object Detection by Box Matching
Zhe Liu, Xiaoqing Ye, Zhikang Zou +5
Multi-modal 3D object detection has received growing attention as the information from different sensors like LiDAR and cameras are complementary. Most fusion methods for 3D detect…
A Large Cross-Modal Video Retrieval Dataset with Reading Comprehension
Weijia Wu, Yuzhong Zhao, Zhuang Li +4
Most existing cross-modal language-to-video retrieval (VR) research focuses on single-modal input from video, i.e., visual representation, while the text is omnipresent in human en…
SOOD: Towards Semi-Supervised Oriented Object Detection
Wei Hua, Dingkang Liang, Jingyu Li +4
Semi-Supervised Object Detection (SSOD), aiming to explore unlabeled data for boosting object detectors, has become an active task in recent years. However, existing SSOD approache…
ICDAR 2023 Video Text Reading Competition for Dense and Small Text
Weijia Wu, Yuzhong Zhao, Zhuang Li +5
Recently, video text detection, tracking, and recognition in natural scenes are becoming very popular in the computer vision community. However, most existing algorithms and benchm…
CrowdCLIP: Unsupervised Crowd Counting via Vision-Language Model
Dingkang Liang, Jiahao Xie, Zhikang Zou +3
Supervised crowd counting relies heavily on costly manual labeling, which is difficult and expensive, especially in dense scenes. To alleviate the problem, we propose a novel unsup…
ICDAR 2023 Competition on Reading the Seal Title
Wenwen Yu, Mingyu Liu, Mingrui Chen +5
Reading seal title text is a challenging task due to the variable shapes of seals, curved text, background noise, and overlapped text. However, this important element is commonly f…
InstMove: Instance Motion for Object-centric Video Segmentation
Qihao Liu, Junfeng Wu, Yi Jiang +3
Despite significant efforts, cutting-edge video segmentation methods still remain sensitive to occlusion and rapid movement, due to their reliance on the appearance of objects in t…
Turning a CLIP Model into a Scene Text Detector
Wenwen Yu, Yuliang Liu, Wei Hua +3
The recent large-scale Contrastive Language-Image Pretraining (CLIP) model has shown great potential in various downstream tasks via leveraging the pretrained vision and language k…
Side Adapter Network for Open-Vocabulary Semantic Segmentation
Mengde Xu, Zheng Zhang, Fangyun Wei +2
This paper presents a new framework for open-vocabulary semantic segmentation with the pre-trained vision-language model, named Side Adapter Network (SAN). Our approach models the…
CAPE: Camera View Position Embedding for Multi-View 3D Object Detection
Kaixin Xiong, Shi Gong, Xiaoqing Ye +5
In this paper, we address the problem of detecting 3D objects from multi-view images. Current query-based methods rely on global 3D position embeddings (PE) to learn the geometric…
StereoDistill: Pick the Cream from LiDAR for Distilling Stereo-based 3D Object Detection
Zhe Liu, Xiaoqing Ye, Xiao Tan +2
In this paper, we propose a cross-modal distillation method named StereoDistill to narrow the gap between the stereo and LiDAR-based approaches via distilling the stereo detectors…
SPTS v2: Single-Point Scene Text Spotting
Yuliang Liu, Jiaxin Zhang, Dezhi Peng +8
End-to-end scene text spotting has made significant progress due to its intrinsic synergy between text detection and recognition. Previous methods commonly regard manual annotation…
The Runner-up Solution for YouTube-VIS Long Video Challenge 2022
Junfeng Wu, Yi Jiang, Qihao Liu +2
This technical report describes our 2nd-place solution for the ECCV 2022 YouTube-VIS Long Video Challenge. We adopt the previously proposed online video instance segmentation metho…
Affinity Feature Strengthening for Accurate, Complete and Robust Vessel Segmentation
Tianyi Shi, Xiaohuan Ding, Wei Zhou +4
Vessel segmentation is crucial in many medical image applications, such as detecting coronary stenoses, retinal vessel diseases and brain aneurysms. However, achieving high pixel-w…
Optimal Boxes: Boosting End-to-End Scene Text Recognition by Adjusting Annotated Bounding Boxes via Reinforcement Learning
Jingqun Tang, Wenming Qian, Luchuan Song +3
Text detection and recognition are essential components of a modern OCR system. Most OCR approaches attempt to obtain accurate bounding boxes of text at the detection stage, which…
When Counting Meets HMER: Counting-Aware Network for Handwritten Mathematical Expression Recognition
Bohan Li, Ye Yuan, Dingkang Liang +5
Recently, most handwritten mathematical expression recognition (HMER) methods adopt the encoder-decoder networks, which directly predict the markup sequences from formula images wi…
In Defense of Online Models for Video Instance Segmentation
Junfeng Wu, Qihao Liu, Yi Jiang +3
In recent years, video instance segmentation (VIS) has been largely advanced by offline models, while online models gradually attracted less attention possibly due to their inferio…
CCPL: Contrastive Coherence Preserving Loss for Versatile Style Transfer
Zijie Wu, Zhen Zhu, Junping Du +1
In this paper, we aim to devise a universally versatile style transfer method capable of performing artistic, photo-realistic, and video style transfer jointly, without seeing vide…