6 papers
Edit2Restore:Few-Shot Image Restoration via Parameter-Efficient Adaptation of Pre-trained Editing Models
M. Akın Yılmaz, Mustafa Akın Yılmaz, Ahmet Bilican +3
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…
Image-Difficulty-Aware Evaluation of Super-Resolution Models
Atakan Topaloglu, Ahmet Bilican, Cansu Korkmaz +1
Image super-resolution models are commonly evaluated by average scores (over some benchmark test sets), which fail to reflect the performance of these models on images of varying d…
Exploring Sparsity for Parameter Efficient Fine Tuning Using Wavelets for Vision
Ahmet Bilican, M. Akın Yılmaz, M. Akın Yılmaz +3
Efficiently adapting large pretrained models is critical under tight compute and memory budgets. While Parameter-Efficient Fine-Tuning (PEFT) methods like LoRA achieve efficiency t…
DiMoSR: Feature Modulation via Multi-Branch Dilated Convolutions for Efficient Image Super-Resolution
M. Akin Yilmaz, Ahmet Bilican, A. Murat Tekalp
Balancing reconstruction quality versus model efficiency remains a critical challenge in lightweight single image super-resolution (SISR). Despite the prevalence of attention mecha…
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…