14 citations · 31 across the 17 of their papers we have counts for
10 papers · 1 filter
Edit2Restore:Few-Shot Image Restoration via Parameter-Efficient Adaptation of Pre-trained Editing Models
Mustafa Akın Yılmaz, Ahmet Bilican, Burak Can Biner +1
Image restoration has traditionally required training specialized models on thousands of paired examples per degradation type. Large pre-trained text-conditioned image editing mode…
Content-Adaptive Inference for State-of-the-art Learned Video Compression
Ahmet Bilican, M. Akın Yılmaz, A. Murat Tekalp
While the BD-rate performance of recent learned video codec models in both low-delay and random-access modes exceed that of respective modes of traditional codecs on average over c…
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…
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…
Multi-Scale Deformable Alignment and Content-Adaptive Inference for Flexible-Rate Bi-Directional Video Compression
M. Akın Yılmaz, O. Ugur Ulas, A. Murat Tekalp
The lack of ability to adapt the motion compensation model to video content is an important limitation of current end-to-end learned video compression models. This paper advances t…
Flexible-Rate Learned Hierarchical Bi-Directional Video Compression With Motion Refinement and Frame-Level Bit Allocation
Eren Cetin, M. Akin Yilmaz, A. Murat Tekalp
This paper presents improvements and novel additions to our recent work on end-to-end optimized hierarchical bi-directional video compression to further advance the state-of-the-ar…
End-to-End Rate-Distortion Optimized Learned Hierarchical Bi-Directional Video Compression
M. Akın Yılmaz, A. Murat Tekalp
Conventional video compression (VC) methods are based on motion compensated transform coding, and the steps of motion estimation, mode and quantization parameter selection, and ent…
Self-Organized Variational Autoencoders (Self-VAE) for Learned Image Compression
M. Akın Yılmaz, Onur Keleş, Hilal Güven +3
In end-to-end optimized learned image compression, it is standard practice to use a convolutional variational autoencoder with generalized divisive normalization (GDN) to transform…
On the Computation of PSNR for a Set of Images or Video
Onur Keleş, M. Akın Yılmaz, A. Murat Tekalp +2
When comparing learned image/video restoration and compression methods, it is common to report peak-signal to noise ratio (PSNR) results. However, there does not exist a generally…
End-to-End Rate-Distortion Optimization for Bi-Directional Learned Video Compression
M. Akin Yilmaz, A. Murat Tekalp
Conventional video compression methods employ a linear transform and block motion model, and the steps of motion estimation, mode and quantization parameter selection, and entropy…