COYO-700M is a large-scale dataset that contains 747M image-text pairs as well as many other meta-attributes to increase the usability to train various models. Our dataset follows a similar strategy to previous vision-and-language datasets, collecting many informative pairs of alt-text and its...
Improving Vision-and-Language Navigation with Image-Text Pairs from the WebVision-and-language navigationTransfer learningEmbodied AIFollowing a navigation instruction such as 'Walk down the stairs and stop at the brown sofa' requires embodied AI agents to ground scene elements referenced via language ...
Therefore, training an effective generalist biomedical model requires high-quality multimodal data, such as parallel image-text pairs. Here, we present PMC-15M, a novel dataset that is two orders of magnitude larger than existing biomedical multimodal datasets such as MIMIC-CXR, and spans a ...
Inspired by this, we propose a novel large-scale multi-modal dataset, named EIT-1M, with over 1 million EEG-image-text pairs. Our dataset is superior in its capacity of reflecting brain activities in simultaneously processing multi-modal information. To achieve this, we collected data pairs ...
We train on a combination of internal datasets, with ≈ 460M image-text pairs, and the publicly available Laion dataset, with ≈ 400M image-text pairs. Experiments 评价FID: image-text数据集用于zero-shot FID的计算(从验证集抽文本作文prompt来生成图像,看其是否和匹配的文本对应)。 主观打分:1. ...
Cross attention or co-attention which involves multi-step of attending to image regions based on text or attending to words based on image [17, 18] can also be applied. However, existing strategies require computational demanding pairwise similarity computation between all image-text pairs with com...
结论:模型训练中image encoder需要选取比较大的,训练数据用到的是0.8B pairs。 -- 03 GIT与当前算法比较 Flamingo 与GIT架构类似,区别是:Image Encoder,Vison Encoder和Text Decoder的参数是冻结的,通过加入其他机制, 如random initialized module,perceiver resampler,使得模型可以学到数据特征。
In recent years, contrastive learning techniques, particularly InfoNCE loss, have propelled advancements in image-text alignment. However, aligning indistinguishable image-text pairs remains a challenge for conventional methods, often overlooking semantically similar content. To overcome these limitations, we ...
Stage2: We train our 1.3B transformer from scratch on 14 million image-text pairs from CC3M [4] and CC12M [5]. For the more detailed model spec, please see configs/dalle-1.3B.yaml. You can download the pretrained models including the tokenizer from this link. This will require about ...
COYO-700M is a large-scale dataset that contains 747M image-text pairs as well as many other meta-attributes to increase the usability to train various models. Our dataset follows a similar strategy to previous vision-and-language datasets, collecting many informative pairs of alt-text and its...