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Any-to-any generation via composable diffusion
Abstract We present Composable Diffusion (CoDi), a novel generative model capable of
generating any combination of output modalities, such as language, image, video, or audio …
generating any combination of output modalities, such as language, image, video, or audio …
Vision transformers are parameter-efficient audio-visual learners
Vision transformers (ViTs) have achieved impressive results on various computer vision
tasks in the last several years. In this work, we study the capability of frozen ViTs, pretrained …
tasks in the last several years. In this work, we study the capability of frozen ViTs, pretrained …
Mavil: Masked audio-video learners
Abstract We present Masked Audio-Video Learners (MAViL) to learn audio-visual
representations with three complementary forms of self-supervision:(1) reconstructing …
representations with three complementary forms of self-supervision:(1) reconstructing …
Vidchapters-7m: Video chapters at scale
Segmenting untrimmed videos into chapters enables users to quickly navigate to the
information of their interest. This important topic has been understudied due to the lack of …
information of their interest. This important topic has been understudied due to the lack of …
Clippo: Image-and-language understanding from pixels only
Multimodal models are becoming increasingly effective, in part due to unified components,
such as the Transformer architecture. However, multimodal models still often consist of many …
such as the Transformer architecture. However, multimodal models still often consist of many …
Valor: Vision-audio-language omni-perception pretraining model and dataset
In this paper, we propose the Vision-Audio-Language Omni-peRception pretraining model
(VALOR) for multimodal understanding and generation. Unlike widely-studied vision …
(VALOR) for multimodal understanding and generation. Unlike widely-studied vision …