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arxiv.org
[2501.03939] Visual question answering: from early ...
Jan 7, 2025 · We review major VQA approaches, focusing on deep learning-based methods, and explore the emerging field of Large Visual Language Models (LVLMs) that have demonstrated success in multimodal tasks like VQA.
zhuanlan.zhihu.com
视觉问答（VQA）顶会论文及常用数据集汇总，CV、NLP交叉领域必看，附...
今天来聊聊计算机视觉和自然语言处理交叉的一个热门研究方向：视觉问答（VQA）。
openaccess.thecvf.com
VQACL: A Novel Visual Question Answering Continual Learning ...
This paper proposes a novel continual learning setting for VQA, which considers multimodal data and compositionality. It also introduces a representation learning method to alleviate forgetting and improve generalization.
blog.csdn.net
视觉问答（VQA）12篇顶会精选论文合集，附常用数据集下载_ocr-vqa数据...
Nov 3, 2023 · 文章浏览阅读4.3k次。 论文提出了一个开放式视觉问答任务：给定图像和问题，回答问题。 问题和回答都是开放式的，问题可以询问图像不同区域的细节。 因此，视觉问答系统通常需要比图像字幕系统对图像有更深入理解和复杂推理。
github.com
GitHub - xiaoman-zhang/PMC-VQA: PMC-VQA is a large-scale ...
PMC-VQA The official codes for PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering
bugerr.github.io
论文阅读：Towards VQA Models That Can Read - CELESTE’S LOG BOOK
Oct 29, 2024 · But today’s VQA models fail catastrophically on questions requiring reading! today’s state-of-art VQA models are predominantly monolithic deep neural networks (without any specialized components).
blog.csdn.net
LLM | 论文精读 | CVPR | 基于问题驱动图像描述的视觉问答增强引言_en...
Nov 8, 2024 · 本文提出了一种增强视觉问答（VQA）性能的新方法，通过生成问题驱动的图像描述作为中间步骤，将上下文信息有效融入到问答过程中，尤其在零样本场景中展现出显著的优势。 研究通过关键词提取技术使描述与问题紧密结合，从而提高了模型的理解和推理能力。