MiaoshouAI/Florence-2-large-PromptGen-v2.0
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Martin Viewegger
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Are you going to release the training code as well (either pretraining or training from scratch)?
7
#4 opened about 1 month ago
by
arpitsh018
Multiple languages support
👍
👀
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#19 opened about 1 month ago
by
thunder-007
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merve's
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about 1 month ago
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3425
New foundation model on image and video captioning just dropped by NVIDIA AI 🔥
Describe Anything Model (DAM) is a 3B vision language model to generate detailed captions with localized references 😮
The team released the models, the dataset, a new benchmark and a demo 🤩 nvidia/describe-anything-680825bb8f5e41ff0785834c
Most of the vision LMs focus on image as a whole, lacking localized references in captions, and not taking in visual prompts (points, boxes, drawings around objects)
DAM addresses this on two levels: new vision backbone that takes in focal crops and the image itself, and a large scale dataset 👀
They generate a dataset by extending existing segmentation and referring expression generation datasets like REFCOCO, by passing in the images and classes to VLMs and generating captions.
Lastly, they also release a new benchmark again with self-supervision, they use an LLM to evaluate the detailed captions focusing on localization 👏
Describe Anything Model (DAM) is a 3B vision language model to generate detailed captions with localized references 😮
The team released the models, the dataset, a new benchmark and a demo 🤩 nvidia/describe-anything-680825bb8f5e41ff0785834c
Most of the vision LMs focus on image as a whole, lacking localized references in captions, and not taking in visual prompts (points, boxes, drawings around objects)
DAM addresses this on two levels: new vision backbone that takes in focal crops and the image itself, and a large scale dataset 👀
They generate a dataset by extending existing segmentation and referring expression generation datasets like REFCOCO, by passing in the images and classes to VLMs and generating captions.
Lastly, they also release a new benchmark again with self-supervision, they use an LLM to evaluate the detailed captions focusing on localization 👏
Finetuning hyperparameters and final training loss
#1 opened about 1 month ago
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Viewegger
Speaker reference from dataset
#2 opened about 2 months ago
by
Viewegger
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Starrail dataset language?
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#1 opened about 2 months ago
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Viewegger
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Introducing open-sourced ClearerVoice-Studio. A powerful speech processing AI tool to dramatically improve your speech quality. Checkout demo page:
alibabasglab/ClearVoice and https://modelscope.cn/studios/iic/ClearerVoice-Studio. Give us a Star on Github: https://github.com/modelscope/ClearerVoice-Studio!
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🎉 ClearerVoice-Studio New Feature: Speech Super-Resolution with MossFormer2 ! 🚀
We’re excited to announce that ClearerVoice-Studio now supports speech super-resolution, powered by our latest MossFormer2-based model!
What’s New?
🔊 Convert Low-Resolution to High-Resolution Audio:
Transform low-resolution audio (effective sampling rate ≥ 16 kHz) into crystal-clear, high-resolution audio at 48 kHz.
🤖 Cutting-Edge Technology:
Leverages the MossFormer2 model plus HiFi-GAN, optimised for generating high-quality audio with enhanced perceptual clarity.
🎧 Enhanced Listening Experience:
Perfect for speech enhancement, content restoration, and high-fidelity audio applications.
🌟 Try It Out!
Upgrade to the latest version of ClearerVoice-Studio (https://github.com/modelscope/ClearerVoice-Studio) to experience this powerful feature. Check out the updated documentation and examples in our repository.
Let us know your thoughts, feedback, or feature requests in the Issues section.
We’re excited to announce that ClearerVoice-Studio now supports speech super-resolution, powered by our latest MossFormer2-based model!
What’s New?
🔊 Convert Low-Resolution to High-Resolution Audio:
Transform low-resolution audio (effective sampling rate ≥ 16 kHz) into crystal-clear, high-resolution audio at 48 kHz.
🤖 Cutting-Edge Technology:
Leverages the MossFormer2 model plus HiFi-GAN, optimised for generating high-quality audio with enhanced perceptual clarity.
🎧 Enhanced Listening Experience:
Perfect for speech enhancement, content restoration, and high-fidelity audio applications.
🌟 Try It Out!
Upgrade to the latest version of ClearerVoice-Studio (https://github.com/modelscope/ClearerVoice-Studio) to experience this powerful feature. Check out the updated documentation and examples in our repository.
Let us know your thoughts, feedback, or feature requests in the Issues section.
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