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Found 4 papers, 2 papers with code
An Improved Upper Bound on the Rate-Distortion Function of Images
Recent work has shown that Variational Autoencoders (VAEs) can be used to upper-bound the information rate-distortion (R-D) function of images, i. e., the fundamental limit of lossy image compression.
An Improved Encoder-Decoder Framework for Food Energy Estimation
Dietary assessment is essential to maintaining a healthy lifestyle.
Long-Tailed Continual Learning For Visual Food Recognition
First, as new foods appear sequentially overtime, a trained model needs to learn the new classes continuously without causing catastrophic forgetting for already learned knowledge of existing food types.
QARV: Quantization-Aware ResNet VAE for Lossy Image Compression
This paper addresses the problem of lossy image compression, a fundamental problem in image processing and information theory that is involved in many real-world applications.
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