MACHINELEARNING_PROGRAMMING Telegram 201
Forwarded from Artificial Intelligence && Deep Learning (Shohruh)
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ImageBind: One Embedding Space To Bind Them All.

PyTorch implementation and pretrained models for ImageBind. For details, see the paper: ImageBind: One Embedding Space To Bind Them All.

ImageBind learns a joint embedding across six different modalities - images, text, audio, depth, thermal, and IMU data. It enables novel emergent applications ‘out-of-the-box’ including cross-modal retrieval, composing modalities with arithmetic, cross-modal detection and generation.

Source code: https://github.com/facebookresearch/imagebind

Paper: https://arxiv.org/pdf/2305.05665v1.pdf

@deeplearning_ai
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ImageBind: One Embedding Space To Bind Them All.

PyTorch implementation and pretrained models for ImageBind. For details, see the paper: ImageBind: One Embedding Space To Bind Them All.

ImageBind learns a joint embedding across six different modalities - images, text, audio, depth, thermal, and IMU data. It enables novel emergent applications ‘out-of-the-box’ including cross-modal retrieval, composing modalities with arithmetic, cross-modal detection and generation.

Source code: https://github.com/facebookresearch/imagebind

Paper: https://arxiv.org/pdf/2305.05665v1.pdf

@deeplearning_ai

BY Computer Science and Programming


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