Scaling Language-Image Pre-training via Maskingarxiv.org/abs/2212.00794 从去年以来,以CLIP为代表的通过语言监督的视觉预训练(Language-supervised Visual Pre-training/ LIP)通过image/text pair的方式打破了传统的视觉预训练依靠超大规模标注数据集的瓶颈。LIP需要依靠超大规模的训练,以文章中的说法,通常在10000...
scaling, which can involve increasing capacity (model scaling) and increasing information (data scaling), is essential for attaining good results in language-supervised training.
In recent years, we have witnessed significant performance boost in the image captioning task based on vision-language pre-training (VLP). Scale is believed to be an important factor for this advance. However, most existing work only focuses on pre-training transformers with m...
Unified Vision-Language Pre-Training for Image Captioning and VQA.pdf You Need Multiple Exiting Dynamic Early Exiting for.pdf Cream Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language Models.pdf VLMO Unified Vision-Language Pre-Training with.pdf DocFo...
scaling research suggests that larger models need more datasets to train efficiently. According to the blog, the team created WebLI—a multilingual language-image dataset made from images and text readily available on the public web—in order to unlock the potential of language-image pretraining. ...
We are able to scale various language, speech and vision models using the Mixture Of Experts technique by incorporating ORT MoE. We will continue to optimize the ORT MoE implementation to improve training throughput and explore new distribution strategies. This will enable d...
training com.microsoft.azure.cognitiveservices.vision.customvision.training.models com.microsoft.azure.cognitiveservices.vision.faceapi com.microsoft.azure.cognitiveservices.vision.faceapi.models com.microsoft.azure.elasticdb.core.commons.transientfaulthandling com.microsoft.azure.elasticdb.query.ex...
BEVBert: Topo-Metric Map Pre-training for Language-guided Navigation Dongyan An, Yuankai Qi, Yangguang Li, Yan Huang, Liangsheng Wang, Tien-Ping Tan, Jing Shao 2022 Improving Vision-and-Language Navigation by Generating Future-View Image Semantics ...
2. A large-scale noisy image-text dataset: 采用类似 CC3M 数据集的收集方法,得到海量 image-text pair,设计了简单的 image- 和 text-based filtering 操作,来进行简单的过滤。 3. Pre-training and Task Transfer: 采用了 dual-encoder 的方式进行 ALIGN 的预训练,该模型也是一种双塔结构。
using-ml-for-disasters.md vision-transformers.md vision_language_pretraining.md vit-align.md vq-diffusion.md warm-starting-encoder-decoder.md wav2vec2-with-ngram.md your-first-ml-project.md zero-deepspeed-fairscale.md zero-shot-eval-on-the-hub.mdBreadcrumbs blog/...