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Found 19 papers, 5 papers with code
Hierarchical Multi-label Text Classification with Horizontal and Vertical Category Correlations
Hierarchical multi-label text classification (HMTC) deals with the challenging task where an instance can be assigned to multiple hierarchically structured categories at the same time.
Multi Label Text Classification
Multi-Label Text Classification
+1
Semantic-Preserving Abstractive Text Summarization with Siamese Generative Adversarial Net
We propose a novel siamese generative adversarial net for abstractive text summarization (SSPGAN), which can preserve the main semantics of the source text.
HRVDA: High-Resolution Visual Document Assistant
In addition, we construct a document-oriented visual instruction tuning dataset and apply a multi-stage training strategy to enhance the model's document modeling capabilities.
Enhancing Visual Document Understanding with Contrastive Learning in Large Visual-Language Models
It can represent that the contrastive learning between the visual holistic representations and the multimodal fine-grained features of document objects can assist the vision encoder in acquiring more effective visual cues, thereby enhancing the comprehension of text-rich documents in LVLMs.
A Challenger to GPT-4V? Early Explorations of Gemini in Visual Expertise
They endow Large Language Models (LLMs) with powerful capabilities in visual understanding, enabling them to tackle diverse multi-modal tasks.
Attention Where It Matters: Rethinking Visual Document Understanding with Selective Region Concentration
We propose a novel end-to-end document understanding model called SeRum (SElective Region Understanding Model) for extracting meaningful information from document images, including document analysis, retrieval, and office automation.
Looking and Listening: Audio Guided Text Recognition
Text recognition in the wild is a long-standing problem in computer vision.
Visual Information Extraction in the Wild: Practical Dataset and End-to-end Solution
We evaluate the existing end-to-end methods for VIE on the proposed dataset and observe that the performance of these methods has a distinguishable drop from SROIE (a widely used English dataset) to our proposed dataset due to the larger variance of layout and entities.
Grab What You Need: Rethinking Complex Table Structure Recognition with Flexible Components Deliberation
Recently, Table Structure Recognition (TSR) task, aiming at identifying table structure into machine readable formats, has received increasing interest in the community.
Turning a CLIP Model into a Scene Text Detector
Recently, pretraining approaches based on vision language models have made effective progresses in the field of text detection.
TaCo: Textual Attribute Recognition via Contrastive Learning
To realize this goal, we design the learning paradigm from three perspectives: 1) generating attribute views, 2) extracting subtle but crucial details, and 3) exploiting valued view pairs for learning, to fully unlock the pre-training potential.
GMN: Generative Multi-modal Network for Practical Document Information Extraction
Document Information Extraction (DIE) has attracted increasing attention due to its various advanced applications in the real world.
OS-MSL: One Stage Multimodal Sequential Link Framework for Scene Segmentation and Classification
In this paper, from an alternate perspective to overcome the above challenges, we unite these two tasks into one task by a new form of predicting shots link: a link connects two adjacent shots, indicating that they belong to the same scene or category.
Sequence-to-Action: Grammatical Error Correction with Action Guided Sequence Generation
The task of Grammatical Error Correction (GEC) has received remarkable attention with wide applications in Natural Language Processing (NLP) in recent years.
Relational Representation Learning in Visually-Rich Documents
To deal with the unpredictable definition of relations, we propose a novel contrastive learning task named Relational Consistency Modeling (RCM), which harnesses the fact that existing relations should be consistent in differently augmented positive views.
The Devil is in the Frequency: Geminated Gestalt Autoencoder for Self-Supervised Visual Pre-Training
The self-supervised Masked Image Modeling (MIM) schema, following "mask-and-reconstruct" pipeline of recovering contents from masked image, has recently captured the increasing interest in the multimedia community, owing to the excellent ability of learning visual representation from unlabeled data.
Neural Collaborative Graph Machines for Table Structure Recognition
We also show that the proposed NCGM can modulate collaborative pattern of different modalities conditioned on the context of intra-modality cues, which is vital for diversified table cases.
Ranked #6 on
Table Recognition
on PubTabNet
NomMer: Nominate Synergistic Context in Vision Transformer for Visual Recognition
For the sake of trade-off between efficiency and performance, a group of works merely perform SA operation within local patches, whereas the global contextual information is abandoned, which would be indispensable for visual recognition tasks.
PuzzleNet: Scene Text Detection by Segment Context Graph Learning
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 bottom-up manner.
