11 citations · 45 across the 20 of their papers we have counts for
20 papers
Improving Scene Graph Generation with Superpixel-Based Interaction Learning
Jingyi Wang, Can Zhang, Jinfa Huang +2
Recent advances in Scene Graph Generation (SGG) typically model the relationships among entities utilizing box-level features from pre-defined detectors. We argue that an overlooke…
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…
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…
TaCo: Textual Attribute Recognition via Contrastive Learning
Chang Nie, Yiqing Hu, Yanqiu Qu +3
As textual attributes like font are core design elements of document format and page style, automatic attributes recognition favor comprehensive practical applications. Existing ap…
GMN: Generative Multi-modal Network for Practical Document Information Extraction
Haoyu Cao, Jiefeng Ma, Antai Guo +5
Document Information Extraction (DIE) has attracted increasing attention due to its various advanced applications in the real world. Although recent literature has already achieved…
OS-MSL: One Stage Multimodal Sequential Link Framework for Scene Segmentation and Classification
Ye Liu, Lingfeng Qiao, Di Yin +4
Scene segmentation and classification (SSC) serve as a critical step towards the field of video structuring analysis. Intuitively, jointly learning of these two tasks can promote e…
Open-Vocabulary Multi-Label Classification via Multi-Modal Knowledge Transfer
Sunan He, Taian Guo, Tao Dai +3
Real-world recognition system often encounters the challenge of unseen labels. To identify such unseen labels, multi-label zero-shot learning (ML-ZSL) focuses on transferring knowl…
RAAT: Relation-Augmented Attention Transformer for Relation Modeling in Document-Level Event Extraction
Yuan Liang, Zhuoxuan Jiang, Di Yin +1
In document-level event extraction (DEE) task, event arguments always scatter across sentences (across-sentence issue) and multiple events may lie in one document (multi-event issu…
Contrastive Graph Multimodal Model for Text Classification in Videos
Ye Liu, Changchong Lu, Chen Lin +2
The extraction of text information in videos serves as a critical step towards semantic understanding of videos. It usually involved in two steps: (1) text recognition and (2) text…
Open Vocabulary Object Detection with Proposal Mining and Prediction Equalization
Peixian Chen, Kekai Sheng, Mengdan Zhang +5
Open-vocabulary object detection (OVD) aims to scale up vocabulary size to detect objects of novel categories beyond the training vocabulary. Recent work resorts to the rich knowle…
Sequence-to-Action: Grammatical Error Correction with Action Guided Sequence Generation
Jiquan Li, Junliang Guo, Yongxin Zhu +4
The task of Grammatical Error Correction (GEC) has received remarkable attention with wide applications in Natural Language Processing (NLP) in recent years. While one of the key p…
Scene Consistency Representation Learning for Video Scene Segmentation
Haoqian Wu, Keyu Chen, Yanan Luo +5
A long-term video, such as a movie or TV show, is composed of various scenes, each of which represents a series of shots sharing the same semantic story. Spotting the correct scene…
Relational Representation Learning in Visually-Rich Documents
Xin Li, Yan Zheng, Yiqing Hu +5
Relational understanding is critical for a number of visually-rich documents (VRDs) understanding tasks. Through multi-modal pre-training, recent studies provide comprehensive cont…
The Devil is in the Frequency: Geminated Gestalt Autoencoder for Self-Supervised Visual Pre-Training
Hao Liu, Xinghua Jiang, Xin Li +3
The self-supervised Masked Image Modeling (MIM) schema, following "mask-and-reconstruct" pipeline of recovering contents from masked image, has recently captured the increasing int…
Knowledge Mining with Scene Text for Fine-Grained Recognition
Hao Wang, Junchao Liao, Tianheng Cheng +5
Recently, the semantics of scene text has been proven to be essential in fine-grained image classification. However, the existing methods mainly exploit the literal meaning of scen…
Head and Body: Unified Detector and Graph Network for Person Search in Media
Xiujun Shu, Yusheng Tao, Ruizhi Qiao +3
Person search in media has seen increasing potential in Internet applications, such as video clipping and character collection. This task is common but overlooked by previous perso…
Neural Collaborative Graph Machines for Table Structure Recognition
Hao Liu, Xin Li, Bing Liu +3
Recently, table structure recognition has achieved impressive progress with the help of deep graph models. Most of them exploit single visual cues of tabular elements or simply com…
NomMer: Nominate Synergistic Context in Vision Transformer for Visual Recognition
Hao Liu, Xinghua Jiang, Xin Li +3
Recently, Vision Transformers (ViT), with the self-attention (SA) as the de facto ingredients, have demonstrated great potential in the computer vision community. For the sake of t…
PuzzleNet: Scene Text Detection by Segment Context Graph Learning
Hao Liu, Antai Guo, Deqiang Jiang +2
Recently, a series of decomposition-based scene text detection methods has achieved impressive progress by decomposing challenging text regions into pieces and linking them in a bo…
Sequence-based Person Attribute Recognition with Joint CTC-Attention Model
Hao Liu, Jingjing Wu, Jianguo Jiang +2
Attribute recognition has become crucial because of its wide applications in many computer vision tasks, such as person re-identification. Like many object recognition problems, va…