53 citations · 202 across the 14 of their papers we have counts for
14 papers
On Versatile Video Coding at UHD with Machine-Learning-Based Super-Resolution
Kristian Fischer, Christian Herglotz, André Kaup
Coding 4K data has become of vital interest in recent years, since the amount of 4K data is significantly increasing. We propose a coding chain with spatial down- and upscaling tha…
Spatially-Adaptive Learning-Based Image Compression with Hierarchical Multi-Scale Latent Spaces
Fabian Brand, Alexander Kopte, Kristian Fischer +1
Adaptive block partitioning is responsible for large gains in current image and video compression systems. This method is able to compress large stationary image areas with only a…
The Bjøntegaard Bible -- Why your Way of Comparing Video Codecs May Be Wrong
Christian Herglotz, Hannah Och, Anna Meyer +8
In this paper, we provide an in-depth assessment on the Bjøntegaard Delta. We construct a large data set of video compression performance comparisons using a diverse set of metrics…
Saliency-Driven Hierarchical Learned Image Coding for Machines
Kristian Fischer, Fabian Brand, Christian Blum +1
We propose to employ a saliency-driven hierarchical neural image compression network for a machine-to-machine communication scenario following the compress-then-analyze paradigm. B…
Learning Frequency-Specific Quantization Scaling in VVC for Standard-Compliant Task-driven Image Coding
Kristian Fischer, Fabian Brand, Christian Herglotz +1
Today, visual data is often analyzed by a neural network without any human being involved, which demands for specialized codecs. For standard-compliant codec adaptations towards ce…
Evaluation of Video Coding for Machines without Ground Truth
Kristian Fischer, Markus Hofbauer, Christopher Kuhn +2
In the emerging field of video coding for machines, video datasets with pristine video quality and high-quality annotations are required for a comprehensive evaluation. However, ex…
Analysis of Neural Image Compression Networks for Machine-to-Machine Communication
Kristian Fischer, Christian Forsch, Christian Herglotz +1
Video and image coding for machines (VCM) is an emerging field that aims to develop compression methods resulting in optimal bitstreams when the decoded frames are analyzed by a ne…
Robust Deep Neural Object Detection and Segmentation for Automotive Driving Scenario with Compressed Image Data
Kristian Fischer, Christian Blum, Christian Herglotz +1
Deep neural object detection or segmentation networks are commonly trained with pristine, uncompressed data. However, in practical applications the input images are usually deterio…
Saliency-Driven Versatile Video Coding for Neural Object Detection
Kristian Fischer, Felix Fleckenstein, Christian Herglotz +1
Saliency-driven image and video coding for humans has gained importance in the recent past. In this paper, we propose such a saliency-driven coding framework for the video coding f…
On Intra Video Coding and In-loop Filtering for Neural Object Detection Networks
Kristian Fischer, Christian Herglotz, André Kaup
Classical video coding for satisfying humans as the final user is a widely investigated field of studies for visual content, and common video codecs are all optimized for the human…
Video Coding for Machines with Feature-Based Rate-Distortion Optimization
Kristian Fischer, Fabian Brand, Christian Herglotz +1
Common state-of-the-art video codecs are optimized to deliver a low bitrate by providing a certain quality for the final human observer, which is achieved by rate-distortion optimi…
Enhanced Image Reconstruction From Quarter Sampling Measurements Using An Adapted Very Deep Super Resolution Network
Simon Grosche, Kristian Fischer, Fabian Brand +2
Quarter sampling is a novel sensor concept that enables the acquisition of higher resolution images without increasing the number of pixels. This is achieved by covering three quar…
Learning True Rate-Distortion-Optimization for End-To-End Image Compression
Fabian Brand, Kristian Fischer, Alexander Kopte +1
Even though rate-distortion optimization is a crucial part of traditional image and video compression, not many approaches exist which transfer this concept to end-to-end-trained i…
Boosting Neural Image Compression for Machines Using Latent Space Masking
Kristian Fischer, Fabian Brand, André Kaup
Today, many image coding scenarios do not have a human as final intended user, but rather a machine fulfilling computer vision tasks on the decoded image. Thereby, the primary goal…