5 papers · 1 filter
FG-DFPN: Flow Guided Deformable Frame Prediction Network
M. Akın Yılmaz, Ahmet Bilican, A. Murat Tekalp
Video frame prediction remains a fundamental challenge in computer vision with direct implications for autonomous systems, video compression, and media synthesis. We present FG-DFP…
A New Multi-Picture Architecture for Learned Video Deinterlacing and Demosaicing with Parallel Deformable Convolution and Self-Attention Blocks
Ronglei Ji, A. Murat Tekalp
Despite the fact real-world video deinterlacing and demosaicing are well-suited to supervised learning from synthetically degraded data because the degradation models are known and…
PAON: A New Neuron Model using Padé Approximants
Onur KeleÅ, A. Murat Tekalp
Convolutional neural networks (CNN) are built upon the classical McCulloch-Pitts neuron model, which is essentially a linear model, where the nonlinearity is provided by a separate…
Saliency-aware End-to-end Learned Variable-Bitrate 360-degree Image Compression
Oguzhan Gungordu, A. Murat Tekalp
Effective compression of 360 images, also referred to as omnidirectional images (ODIs), is of high interest for various virtual reality (VR) and related applications. 2D im…
Motion-Adaptive Inference for Flexible Learned B-Frame Compression
M. Akin Yilmaz, O. Ugur Ulas, Ahmet Bilican +1
While the performance of recent learned intra and sequential video compression models exceed that of respective traditional codecs, the performance of learned B-frame compression m…