Learned image coding for machines: A content-adaptive approach
Today, according to the Cisco Annual Internet Report (2018-2023), the fastest-growing
category of Internet traffic is machine-to-machine communication. In particular, machine-to …
category of Internet traffic is machine-to-machine communication. In particular, machine-to …
Universal deep image compression via content-adaptive optimization with adapters
Deep image compression performs better than conventional codecs, such as JPEG, on
natural images. However, deep image compression is learning-based and encounters a …
natural images. However, deep image compression is learning-based and encounters a …
Towards hybrid-optimization video coding
Video coding that pursues the highest compression efficiency is the art of computing for rate-
distortion optimization. The optimization has been approached in different ways, exemplified …
distortion optimization. The optimization has been approached in different ways, exemplified …
Instance-adaptive video compression: Improving neural codecs by training on the test set
We introduce a video compression algorithm based on instance-adaptive learning. On each
video sequence to be transmitted, we finetune a pretrained compression model. The optimal …
video sequence to be transmitted, we finetune a pretrained compression model. The optimal …
Quality assessment of higher resolution images and videos with remote testing
In many research fields, human-annotated data plays an important role as it is used to
accomplish a multitude of tasks. One such example is in the field of multimedia quality …
accomplish a multitude of tasks. One such example is in the field of multimedia quality …
Performance evaluation of objective image quality metrics on conventional and learning-based compression artifacts
Lossy image compression is a popular, simple and effective solution to reduce the amount of
data representing digital pictures. In most lossy compression methods, the reduced volume …
data representing digital pictures. In most lossy compression methods, the reduced volume …
Harnessing Meta-Learning for Improving Full-Frame Video Stabilization
Video stabilization is a longstanding computer vision problem particularly pixel-level
synthesis solutions for video stabilization which synthesize full frames add to the complexity …
synthesis solutions for video stabilization which synthesize full frames add to the complexity …
Reducing the amortization gap of entropy bottleneck in end-to-end image compression
End-to-end deep trainable models are about to exceed the performance of the traditional
handcrafted compression techniques on videos and images. The core idea is to learn a non …
handcrafted compression techniques on videos and images. The core idea is to learn a non …
Content-adaptive convolutional neural network post-processing filter
Neural Network (NN)-based coding techniques are being developed for hybrid video coding
schemes, such as the Versatile Video Coding (VVC) standard. In-loop filters and …
schemes, such as the Versatile Video Coding (VVC) standard. In-loop filters and …
Adaptation and attention for neural video coding
Neural image coding represents now the state-of-the-art image compression approach.
However, a lot of work is still to be done in the video domain. In this work, we propose an …
However, a lot of work is still to be done in the video domain. In this work, we propose an …