Sora: A review on background, technology, limitations, and opportunities of large vision models
Sora is a text-to-video generative AI model, released by OpenAI in February 2024. The
model is trained to generate videos of realistic or imaginative scenes from text instructions …
model is trained to generate videos of realistic or imaginative scenes from text instructions …
mplug-2: A modularized multi-modal foundation model across text, image and video
Recent years have witnessed a big convergence of language, vision, and multi-modal
pretraining. In this work, we present mPLUG-2, a new unified paradigm with modularized …
pretraining. In this work, we present mPLUG-2, a new unified paradigm with modularized …
Unmasked teacher: Towards training-efficient video foundation models
Abstract Video Foundation Models (VFMs) have received limited exploration due to high
computational costs and data scarcity. Previous VFMs rely on Image Foundation Models …
computational costs and data scarcity. Previous VFMs rely on Image Foundation Models …
Vast: A vision-audio-subtitle-text omni-modality foundation model and dataset
Vision and text have been fully explored in contemporary video-text foundational models,
while other modalities such as audio and subtitles in videos have not received sufficient …
while other modalities such as audio and subtitles in videos have not received sufficient …
Towards open vocabulary learning: A survey
In the field of visual scene understanding, deep neural networks have made impressive
advancements in various core tasks like segmentation, tracking, and detection. However …
advancements in various core tasks like segmentation, tracking, and detection. However …
Valor: Vision-audio-language omni-perception pretraining model and dataset
In this paper, we propose a Vision-Audio-Language Omni-peRception pretraining model
(VALOR) for multi-modal understanding and generation. Different from widely-studied vision …
(VALOR) for multi-modal understanding and generation. Different from widely-studied vision …
Languagebind: Extending video-language pretraining to n-modality by language-based semantic alignment
The video-language (VL) pretraining has achieved remarkable improvement in multiple
downstream tasks. However, the current VL pretraining framework is hard to extend to …
downstream tasks. However, the current VL pretraining framework is hard to extend to …
A simple recipe for contrastively pre-training video-first encoders beyond 16 frames
Understanding long real-world videos requires modeling of long-range visual
dependencies. To this end we explore video-first architectures building on the common …
dependencies. To this end we explore video-first architectures building on the common …
Distilling vision-language models on millions of videos
The recent advance in vision-language models is largely attributed to the abundance of
image-text data. We aim to replicate this success for video-language models but there …
image-text data. We aim to replicate this success for video-language models but there …
Multimodal large language models: A survey
J Wu, W Gan, Z Chen, S Wan… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
The exploration of multimodal language models integrates multiple data types, such as
images, text, language, audio, and other heterogeneity. While the latest large language …
images, text, language, audio, and other heterogeneity. While the latest large language …