[MMSP 2023, PCS 2024]
[ICIP 2024] Lightweight distribution compression for neural image compression
Official PyTorch implementation of AFP-GIC: controllable generative image compression with a single model for multiple bitrates.
Implementacija ključnih komponenti JND-LIC metode (Pan et al., 2025) zasnovana na CompressAI baseline-u, sa evaluacijom na portretima iz CelebA-HQ
Deep Learning model for compressing UI screenshots when a related reference screenshot exists. Compares conventional codecs with learned no-reference and reference-conditioned codecs on 24k WebSight-derived pairs, with a local demo and a mode selector that falls back to no-reference.
NeuroPack is a research-oriented neural compression toolkit for 3D microscopy volumes.
Proof of Concept (POC): A research protocol for semantic transmission over noisy channels using pre-trained neural codecs. Not production-ready.
The following project is an analytical analysis which compares deep learned image compression (CompressAI, Conv2D Autoencoder) against traditional codecs (JPEG, PNG) on CIFAR-10 on the basis of the benchmarks: rate-distortion and latency.
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