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Found 7 papers, 1 papers with code
Designs and Implementations in Neural Network-based Video Coding
The past decade has witnessed the huge success of deep learning in well-known artificial intelligence applications such as face recognition, autonomous driving, and large language model like ChatGPT.
Revisiting the Sample Adaptive Offset post-filter of VVC with Neural-Networks
The Sample Adaptive Offset (SAO) filter has been introduced in HEVC to reduce general coding and banding artefacts in the reconstructed pictures, in complement to the De-Blocking Filter (DBF) which reduces artifacts at block boundaries specifically.
Neural Network based Inter bi-prediction Blending
This paper presents a learning-based method to improve bi-prediction in video coding.
Combined neural network-based intra prediction and transform selection
The interactions between different tools added successively to a block-based video codec are critical to its rate-distortion efficiency.
Iterative training of neural networks for intra prediction
This paper presents an iterative training of neural networks for intra prediction in a block-based image and video codec.
Context-adaptive neural network based prediction for image compression
Unlike the H. 265 intra prediction modes, which are each specialized in predicting a specific texture, the proposed PNNS can model a large set of complex textures.
Autoencoder based image compression: can the learning be quantization independent?
Usually, the rate-distortion performances of image compression are tuned by varying the quantization step size.
