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README.md
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# CapDec - NoiseLevel: 0.015
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Their method aims to train CLIP with only text samples. Therefore they are injecting zero-mean Gaussian Noise into the text embeddings before decoding.
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The reported metrics are results of a model with a Noise Variance of 0.016, which the authors unfortunately do not provide in their repository.
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This model with a Noise Variance 0.015 is the closest available pre-trained model to their best model.
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## Performance
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The authors don't explicitly report the performance for this NoiseLevel but it can be estimated from the following figure from the original paper:
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# CapDec - NoiseLevel: 0.015
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## Model Description
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These are model weights originally provided by the authors of the paper [Text-Only Training for Image Captioning using Noise-Injected CLIP](https://arxiv.org/pdf/2211.00575.pdf).
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Their method aims to train CLIP with only text samples. Therefore they are injecting zero-mean Gaussian Noise into the text embeddings before decoding.
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The reported metrics are results of a model with a Noise Variance of 0.016, which the authors unfortunately do not provide in their repository.
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This model with a Noise Variance 0.015 is the closest available pre-trained model to their best model.
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## Datasets
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The authors trained the model on MS-COCO and Flickr30k datasets.
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## Performance
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The authors don't explicitly report the performance for this NoiseLevel but it can be estimated from the following figure from the original paper:
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![](capdec_performance.png)
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