然后提出了GLIP模型:Grounded Language-Image Pre-training。 GLIP的主要贡献如下: 将phrase grounding和目标检测任务统一,将image和text prompt同时输入到目标检测网络中,prompt中带有图片中所有类别的详细描述。 GLIP采用了丰富的预训练数据,使得它的预训练模型可以更轻松地迁移到下游任务中。预训练的GLIP在COCO数据集...
这个任务是学习object-level,语言感知和语义丰富的视觉表示的有效和可扩展的预训练任务,并提出了Grounded Language-Image Pre-training(GLIP)。我们的方法统一了phrase grounding和object detection任务,object detection可以被转换为上下文无关的phrase grounding,而phrase grounding可以被视为置于context背景下的的object ...
GLIP-T (C) is pre-trained on 1) O365 and 2) GoldG, 0.8M human-annotated gold grounding data curated by MDETR [23], including Flickr30K, VG Caption [28], and GQA [19]. We have removed COCO images from the dataset. It is designed to verify the effectiveness of gold grounding dat...
GLIPv1: Grounded Language-Image Pre-training GLIPv2: Unifying Localization and VL Understanding 代码地址:https://github.com/microsoft/GLIP 论文地址1:https://paperswithcode.com/paper/grounded-language-image-pre-training 论文地址2:https://arxiv.org/abs/2206.05836 翻译1https://zhuanlan.zhihu.com/...
Grounded Language-Image Pre-training(GLIP)是一种基于语言和图像的预训练方法,旨在为下游自然语言处理(NLP)和计算机视觉(CV)任务提供有用的特征表示。该方法通过对大规模文本和图像数据进行联合学习,使得模型能够将视觉信息与语言知识相结合。 3.2 代码功能与实现原理 GLIP代码的主要功能是实现了语言和图像之间的联合...
This paper presents a grounded language-image pre-training (GLIP) model for learning object-level, language-aware, and semantic-rich visual representations. GLIP unifies object detection and phrase grounding for pre-training. The unification brings two benefits: 1) it allows GLIP to learn from ...
GLIP:Grounded Language-Image Pre-training 当前视觉识别任务通常受限于预定义类别范围,限制了其在真实场景应用的扩展。CLIP的出现打破了这一限制,通过利用图文对进行训练,使模型能够根据文本提示识别任意类别,这在分类任务上表现优秀。GLIP则试图将这一技术应用于目标检测等复杂任务中,创新性地引入了...
GLIP: Grounded Language-Image Pre-training Updates 01/17/2023: From image understanding to image generation for open-set grounding? Check out GLIGEN (Grounded Language-to-Image Generation) GLIGEN: (box, concept) → image || GLIP: image → (box, concept) 09/19/2022: GLIPv2 has been ...
探索视觉领域的革新,GLIP——Grounded Language-Image Pre-training,以突破性的技术引领我们进入一个全新的视觉识别时代。相较于传统的界限,CLIP和GLIP以image-text联合学习的方式,为各种任务带来了革命性的提升。其中,GLIP的独到之处在于其phrase grounding概念的引入,将目标检测与词义定位完美融合,...
GLIP (Grounded Language-Image Pre-training) is a generalizable object detection (we use object detection as the representative of localization tasks) model. As illustrated in Figure 1, it is language aware, taking a natural language prompt as instruction. It is also semantic...