(2023c). "Minigpt-v2: Large Language Model as a Unified Interface for Vision-Language Multi-Task Learning." arXiv preprint arXiv:2310.09478. InternVL:Chen, Z., et al. (2023c). "Internvl: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks." arXiv ...
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对于参考定位和定位字幕双重任务,我们从GRIT(Peng et al., 2023)、Visual Genome(Krishna et al., 2017)、RefCOCO(Kazemzadeh et al., 2014)、RefCOCO+和RefCOCOg(Mao et al.,2016)构建训练样本。为了改进面向文本的任务,我们从Common Crawl2收集pdf和HTML格式数据,并遵循Kim等(2022)在英语和中文中生成带有...
foundationgptlanguage-modelmultimodalmulti-modalityvision-transformergpt-4visual-language-learningllmchatgptinstruction-tuninglarge-language-modelsupervised-finetuningmllmvision-language-modellarge-vision-language-model UpdatedJan 22, 2025 Python PKU-YuanGroup/MoE-LLaVA ...
DriveVLM接受图像序列作为输入,并通过CoT机制输出场景描述、场景分析和分层规划结果。 DriveVLM-Dual进一步整合了传统的3D感知和轨迹规划模块,以实现空间推理能力和实时轨迹规划。 任务定义 数据集构建 Experiment 使用通义千问的VLM作为BaseModel,参数量总共9.6B (visual encoder 1.9B, llm 7.7B, align 0.08B) ...
3.2 VISUALQUESTIONANSWERING 视觉问答是一项验证模型通用多模态能力的任务,需要掌握视觉语言理解和常识推理等技能。我们在7个VQA基准上评估我们的模型:VQAv2、OKVQA、GQA、VizWiz QA、OCRVQA、TextVQA、ScienceQA,涵盖了广泛的视觉场景。我们在训练集上训练我们的基础模型,并在所有基准的公开可用的val/test集上对其进行...
1c). These models allow users to perform visual question answering96,97: users can upload an image and ask questions about it, which the model interprets and responds to accordingly. Fig. 1: Overview of domains, tasks, approach and models. a, Example images for the different experiments. ...
More efficient training: Large language and visual models can be trained separately and then combined, which can be more efficient than training a single large model from scratch. This is because training a large model from scratch can be computationally intensive and time-consuming while training ...
The development of Large Vision-Language Models (LVLMs) is striving to catch up with the success of Large Language Models (LLMs), yet it faces more challenges to be resolved. Very recent works enable LVLMs to localize object-level visual contents and ground text to them. Nonetheless, ...
In Large Visual Language Models (LVLMs), the efficacy of In-Context Learning (ICL) remains limited by challenges in cross-modal interactions and representation disparities. To overcome these challenges, we introduce a novel Visual In-Context Learning (VICL) method comprising Visual Demonstration ...