High-Fidelity Mural Restoration via a Unified Hybrid Mask-Aware Transformer
Ancient murals are valuable cultural artifacts, but many have suffered severe degradation due to environmental exposure, material aging, and human activity. Restoring these artworks is challenging because it requires both reconstructing large missing structures and preserving authentic, undamaged regions. We present the Hybrid Mask-Aware Transformer (HMAT), a unified framework for high-fidelity mural restoration that addresses both structural completion and authentic-region preservation. HMAT integrates Mask-Aware Dynamic Filtering for robust local texture modeling with a Transformer bottleneck for long-range structural inference, enabling recovery of continuous line patterns and coherent...
| Authors | Jincheng Jiang, Qianhao Han, Chi Zhang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 5 April 2026 |
| Last updated at source | 16 July 2026 |
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