Compressed Video Super-Resolution based on Hierarchical Encoding
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866912436037091328 |
|---|---|
| author | Jiang, Yuxuan Teng, Siyue Zhu, Qiang Feng, Chen Zeng, Chengxi Zhang, Fan Zhu, Shuyuan Zeng, Bing Bull, David |
| author_facet | Jiang, Yuxuan Teng, Siyue Zhu, Qiang Feng, Chen Zeng, Chengxi Zhang, Fan Zhu, Shuyuan Zeng, Bing Bull, David |
| contents | This paper presents a general-purpose video super-resolution (VSR) method, dubbed VSR-HE, specifically designed to enhance the perceptual quality of compressed content. Targeting scenarios characterized by heavy compression, the method upscales low-resolution videos by a ratio of four, from 180p to 720p or from 270p to 1080p. VSR-HE adopts hierarchical encoding transformer blocks and has been sophisticatedly optimized to eliminate a wide range of compression artifacts commonly introduced by H.265/HEVC encoding across various quantization parameter (QP) levels. To ensure robustness and generalization, the model is trained and evaluated under diverse compression settings, allowing it to effectively restore fine-grained details and preserve visual fidelity. The proposed VSR-HE has been officially submitted to the ICME 2025 Grand Challenge on VSR for Video Conferencing (Team BVI-VSR), under both the Track 1 (General-Purpose Real-World Video Content) and Track 2 (Talking Head Videos). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_14381 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Compressed Video Super-Resolution based on Hierarchical Encoding Jiang, Yuxuan Teng, Siyue Zhu, Qiang Feng, Chen Zeng, Chengxi Zhang, Fan Zhu, Shuyuan Zeng, Bing Bull, David Image and Video Processing Computer Vision and Pattern Recognition This paper presents a general-purpose video super-resolution (VSR) method, dubbed VSR-HE, specifically designed to enhance the perceptual quality of compressed content. Targeting scenarios characterized by heavy compression, the method upscales low-resolution videos by a ratio of four, from 180p to 720p or from 270p to 1080p. VSR-HE adopts hierarchical encoding transformer blocks and has been sophisticatedly optimized to eliminate a wide range of compression artifacts commonly introduced by H.265/HEVC encoding across various quantization parameter (QP) levels. To ensure robustness and generalization, the model is trained and evaluated under diverse compression settings, allowing it to effectively restore fine-grained details and preserve visual fidelity. The proposed VSR-HE has been officially submitted to the ICME 2025 Grand Challenge on VSR for Video Conferencing (Team BVI-VSR), under both the Track 1 (General-Purpose Real-World Video Content) and Track 2 (Talking Head Videos). |
| title | Compressed Video Super-Resolution based on Hierarchical Encoding |
| topic | Image and Video Processing Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2506.14381 |