Enhancing Quality for VVC Compressed Videos by Jointly Exploiting Spatial Details and Temporal Structure
This work addresses video compression quality enhancement for applications like streaming, but it appears incremental as it builds on existing methods without introducing a new paradigm.
The paper tackles the problem of enhancing the quality of VVC compressed videos by jointly exploiting spatial details and temporal structure, resulting in improved reconstruction quality as demonstrated by experimental results.
In this paper, we propose a quality enhancement network of versatile video coding (VVC) compressed videos by jointly exploiting spatial details and temporal structure (SDTS). The proposed network consists of a temporal structure fusion subnet and a spatial detail enhancement subnet. The former subnet is used to estimate and compensate the temporal motion across frames, and the latter subnet is used to reduce the compression artifacts and enhance the reconstruction quality of compressed video. Experimental results demonstrate the effectiveness of our SDTS-based method.