Vision-language pre-training: Basics, recent advances, and future trends
This monograph surveys vision-language pre-training (VLP) methods for multimodal
intelligence that have been developed in the last few years. We group these approaches …
intelligence that have been developed in the last few years. We group these approaches …
[HTML][HTML] Large-scale multi-modal pre-trained models: A comprehensive survey
With the urgent demand for generalized deep models, many pre-trained big models are
proposed, such as bidirectional encoder representations (BERT), vision transformer (ViT) …
proposed, such as bidirectional encoder representations (BERT), vision transformer (ViT) …
Scalable 3d captioning with pretrained models
We introduce Cap3D, an automatic approach for generating descriptive text for 3D objects.
This approach utilizes pretrained models from image captioning, image-text alignment, and …
This approach utilizes pretrained models from image captioning, image-text alignment, and …
Filip: Fine-grained interactive language-image pre-training
Unsupervised large-scale vision-language pre-training has shown promising advances on
various downstream tasks. Existing methods often model the cross-modal interaction either …
various downstream tasks. Existing methods often model the cross-modal interaction either …
Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts
The availability of large-scale image captioning and visual question answering datasets has
contributed significantly to recent successes in vision-and-language pre-training. However …
contributed significantly to recent successes in vision-and-language pre-training. However …
Transformers in vision: A survey
Astounding results from Transformer models on natural language tasks have intrigued the
vision community to study their application to computer vision problems. Among their salient …
vision community to study their application to computer vision problems. Among their salient …
X-clip: End-to-end multi-grained contrastive learning for video-text retrieval
Video-text retrieval has been a crucial and fundamental task in multi-modal research. The
development of video-text retrieval has been considerably promoted by large-scale multi …
development of video-text retrieval has been considerably promoted by large-scale multi …
Vinvl: Revisiting visual representations in vision-language models
This paper presents a detailed study of improving vision features and develops an improved
object detection model for vision language (VL) tasks. Compared to the most widely used …
object detection model for vision language (VL) tasks. Compared to the most widely used …
From show to tell: A survey on deep learning-based image captioning
Connecting Vision and Language plays an essential role in Generative Intelligence. For this
reason, large research efforts have been devoted to image captioning, ie describing images …
reason, large research efforts have been devoted to image captioning, ie describing images …
Gloria: A multimodal global-local representation learning framework for label-efficient medical image recognition
In recent years, the growing number of medical imaging studies is placing an ever-
increasing burden on radiologists. Deep learning provides a promising solution for …
increasing burden on radiologists. Deep learning provides a promising solution for …