[Submitted on 11 Oct 2026 (v1), last revised 14 Oct 2026 (this version, v2)]
Abstract:Recovering visually faithful content from damaged video bitstreams is important for reliable multimedia communication and storage. Existing methods exploit local residuals and non-local RGB references of the input video sequence, but both sources can become unreliable after decoding, while processing additional references increases receiver computation and memory. This paper studies multimodal bitstream-corrupted video recovery (MBSCVR) using RGB and depth information, where pre-transmission depth-based geometry aids reconstruction when the received appearance is corrupted. We propose a novel MBSCVR framework that selects and effectively utilizes a single selected non-local RGB reference per recovery window to achieve higher performance. It integrates a reliability-aware multimodal selector that combines valid appearance with depth compatibility before reference encoding. Depth-Conditioned Reference Adaptation (DCRA) introduces selected RGB evidence into feature completion and content generation, while frame-aligned depth conditions completion queries. On the complete BSCV benchmark with oracle masks, MBSCVR uses one selected reference to achieve 32.30 dB on YouTube-VOS and 28.93 dB on DAVIS, surpassing full-reference B2SCVR by 0.27 and 0.33 dB and improving SSIM on both subsets. Matched receiver-forward measurements show 36.8% lower latency and 40.8% lower peak memory. These results demonstrate how compact geometric guidance and adapted appearance processing improve the quality–resource trade-off of multimedia recovery.
Submission history
From: Tianyi Liu [view email]
[v1] Sun, 11 Oct 2026 17:52:09 UTC (2,288 KB)
[v2] Wed, 14 Oct 2026 15:06:06 UTC (2,288 KB)
