XavierXiao/Dreambooth-Stable-Diffusion
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Once the subject is embedded in the output domain of the model, the unique identifier can then be used to synthesize fully-novel photorealistic images of the subject contextualized in different scenes.
guytevet/motion-diffusion-model
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In this paper, we introduce Motion Diffusion Model (MDM), a carefully adapted classifier-free diffusion-based generative model for the human motion domain.
This simple framework requires no prompts or verbalizers, and achieves high accuracy with orders of magnitude less parameters than existing techniques.
wpeebles/g.pt
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We explore a data-driven approach for learning to optimize neural networks.
openai/whisper
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Preprint 2022
We study the capabilities of speech processing systems trained simply to predict large amounts of transcripts of audio on the internet.
Ranked #1 on
Speech Recognition
on CHiME6
We test both task-specific and general baselines, evaluating downstream performance in addition to the ability of the models to provide provenance.
Ranked #3 on
Entity Linking
on KILT: WNED-CWEB
salesforce/lavis
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We introduce LAVIS, an open-source deep learning library for LAnguage-VISion research and applications.
zinengtang/tvlt
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In this work, we present the Textless Vision-Language Transformer (TVLT), where homogeneous transformer blocks take raw visual and audio inputs for vision-and-language representation learning with minimal modality-specific design, and do not use text-specific modules such as tokenization or automatic speech recognition (ASR).
towhee-io/towhee
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Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
shengyu-meng/dreamfields-3D
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CVPR 2022
Our method, Dream Fields, can generate the geometry and color of a wide range of objects without 3D supervision.
