Atefeh Khoshkhahtinat — accepted AI-conference papers

2025

Integrated Global-Local Gaussian Attention for Image Compression

ICASSP 2025accepted

Transformers have demonstrated outstanding performance in learned image compression (LIC) due to their high capacity for modeling complex dependencies. However, existing methods employ window-based attention mechanisms to reduce overhead, which limits the long-range dependency modeling capabilities…

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2024

Laplacian-guided Entropy Model in Neural Codec with Blur-dissipated Synthesis

Atefeh Khoshkhahtinat, Ali Zafari, Piyush M. Mehta, Nasser M. Nasrabadi

CVPR 2024poster

While replacing Gaussian decoders with a conditional diffusion model enhances the perceptual quality of reconstructions in neural image compression their lack of inductive bias for image data restricts their ability to achieve state-of-the-art perceptual levels. To address this limitation we adopt a…

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