H. Esfahanizadeh

Experiments show that the proposed framework significantly improves robustness over baseline DCVC-RT under packet erasures, achieving graceful degradation in less important regions while better preserving task-relevant visual content.

A single learned codec can adapt to diverse tasks on-the-fly, achieving near task-specific performance without retraining.

Spatial-domain JSCC excels at localized loss recovery, but feature-domain JSCC outshines in maintaining fidelity during distributed erasures.