(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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multi-modality instruction-following in-context-learning large-language-models chain-of-thought instruction-tuning visual-instruction-tuning large-vision-language-model multimodal-instruction-tuning large-vision-language-models multimodal-large-language-models multimodal-in-context-learning multimodal-chain-of-tho...
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...
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 ...
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) ...
3.3 VISUALGROUNDING 为了赋予我们的模型一致且交互式的视觉定位能力,我们收集了一个高质量的数据集,涵盖了4种类型的定位数据:(1)定位说明文字(GC)——图像说明文字数据集,其中说明文字中的每个名词短语后面都有相应的参考边界框;(2)引用表达式生成(REG)——面向图像的数据集,图像中的每个边界框都用描述性文本表达式...
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 Retrie...
large-scale datasets such as LAION400M and COYO700M. We employ sample-to-cluster contrastive learning to optimize performance. Our models have been thoroughly validated across various tasks, including multimodal visual large language models (e.g., LLaVA), image retrieval, and image classification....
One example would be to contrast OpenAI products like ChatGPT and Sora against each other. An LLM like ChatGPT is great at generating text that sounds human-like and understanding complex language patterns. Other AI systems like Sora have visual patches that generate videos from text prompts, me...