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20212026
most citedVisual-Semantic Transformer for Scene Text Recognition

11 citations · 12 across the 6 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

Learning to Look Again: Loss-Gap Supervision for Free-form Crop Routing in Vision-Language Models

Jinchang Zhu, Rong Fu, Yi Ding +3

Vision-language models (VLMs) fail many detail-centric questions for a concrete reason: the answer is visible in the image, yet lost after the image is compressed into a low-resolu…

cs.CV2026

Mema: Memory-Augmented Adapter for Enhanced Vision-Language Understanding

Ying Liu, Yudong Han, Kean Shi +1

Multimodal Large Language Models (MLLMs) have achieved remarkable performance by aligning pretrained visual representations with the linguistic knowledge embedded in Large Language…

cs.CV2026

MeDocVL: A Visual Language Model for Medical Document Understanding and Parsing

Wenjie Wang, Wei Wu, Ying Liu +10

Medical document OCR is challenging due to complex layouts, domain-specific terminology, and noisy annotations, while requiring strict field-level exact matching. Existing OCR syst…

cs.CV2025

Team PA-VCG's Solution for Competition on Understanding Chinese College Entrance Exam Papers in ICDAR'25

Wei Wu, Wenjie Wang, Yang Tan +6

This report presents Team PA-VGG's solution for the ICDAR'25 Competition on Understanding Chinese College Entrance Exam Papers. In addition to leveraging high-resolution image proc…

cs.CV2025★ 1 cited

Fine-Grained Open-Vocabulary Object Detection with Fined-Grained Prompts: Task, Dataset and Benchmark

Ying Liu, Yijing Hua, Haojiang Chai +2

Open-vocabulary detectors are proposed to locate and recognize objects in novel classes. However, variations in vision-aware language vocabulary data used for open-vocabulary learn…

cs.CV2021★ 11 cited

Visual-Semantic Transformer for Scene Text Recognition

Xin Tang, Yongquan Lai, Ying Liu +2

Modeling semantic information is helpful for scene text recognition. In this work, we propose to model semantic and visual information jointly with a Visual-Semantic Transformer (V…