| --- |
| license: cc-by-nc-4.0 |
| task_categories: |
| - video-to-video |
| language: |
| - en |
| tags: |
| - computer-vision |
| - video-restoration |
| - video-dereflection |
| - reflection-removal |
| - benchmark |
| - 4k-video |
| size_categories: |
| - n<1K |
| pretty_name: S2R-Bench |
| --- |
| |
| # S2R-Bench |
|
|
| S2R-Bench is a real-world video reflection removal benchmark introduced in **[From Synthesis to Removal: |
| Physics-Grounded Reflection Simulation and Diffusion-Based Video Dereflection](https://arxiv.org/abs/2608.11562)**. It evaluates whether a video dereflection method can recover a temporally consistent transmission layer from videos recorded through reflective glass. |
|
|
| The benchmark contains two complementary test sets: |
|
|
| - **S2R-Ref**: 60 real captured video pairs constructed from the [DRR dataset](https://github.com/Abuuu122/Dereflection-Any-Image), each containing a reflection-contaminated input and its reflection-free transmission-layer ground truth. |
| - **S2R-Real**: 50 in-the-wild reflection-contaminated videos without ground truth, intended for qualitative and no-reference evaluation. |
|
|
| > **Attention:** S2R-Ref is constructed from the **training split** of the DRR dataset. |
| > Therefore, it may not provide an accurate measure of generalization for methods trained on DRR, |
| > as those methods may have seen the underlying training data during development. |
| > Results on S2R-Ref should be interpreted with this potential data overlap in mind. |
|
|
|
|
| ## Dataset Details |
|
|
| Video reflection removal separates a video recorded through glass into a desired transmission layer and an unwanted reflection layer. In addition to the challenges of single-image reflection removal, a video method must preserve temporal consistency under camera motion, scene motion, spatially varying reflections, blur, ghosting, and different reflection strengths. |
|
|
| | Subset | Input videos | Ground truth | Primary use | |
| |---|---:|---:|---| |
| | S2R-Ref | 60 | 60 paired transmission videos | Full-reference quantitative and qualitative evaluation | |
| | S2R-Real | 50 | Not available | Real-world qualitative and no-reference evaluation | |
|
|
| ## Qualitative Examples |
|
|
| ### S2R-Ref |
|
|
| <p align="center"> |
| <img src="https://codingwzp.github.io/VideoDereflection_S2R/static/images/fig7_s2r_ref.jpg" alt="Qualitative comparison on the S2R-Ref benchmark" width="100%"> |
| </p> |
|
|
| <p align="center"><em>Qualitative comparison on the S2R-Ref benchmark. Image from the project homepage.</em></p> |
|
|
| ### S2R-Real |
|
|
| <p align="center"> |
| <img src="https://codingwzp.github.io/VideoDereflection_S2R/static/images/fig8_s2r_real.jpg" alt="Qualitative comparison on the S2R-Real benchmark" width="100%"> |
| </p> |
|
|
| <p align="center"><em>Qualitative comparison on the S2R-Real benchmark. Image from the project homepage.</em></p> |
|
|
| - **Homepage:** https://codingwzp.github.io/VideoDereflection_S2R/ |
| - **Paper:** https://arxiv.org/abs/2608.11562 |
| - **Task:** Video reflection removal / video dereflection |
| - **License:** Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) |
| |
| ## Dataset Structure |
| |
| ```text |
| S2R-Bench/ |
| |-- S2R-Ref/ |
| | |-- blended/ # Reflection-contaminated input videos |
| | `-- transmission_layer/ # Paired reflection-free ground truth |
| `-- S2R-Real/ |
| `-- blended/ # In-the-wild input videos without ground truth |
| ``` |
| |
| For **S2R-Ref**, an input video and its ground-truth transmission video share the same filename: |
|
|
| ```text |
| S2R-Ref/blended/DSC_0006.mp4 |
| S2R-Ref/transmission_layer/DSC_0006.mp4 |
| ``` |
|
|
| Use the filename stem as the sample identifier when matching predictions to ground truth. Each file in `S2R-Real/blended/` is an independent test sequence. |
|
|
|
|
| ## Citation |
|
|
| If you use S2R-Bench, please cite the S2R paper: |
|
|
| ```bibtex |
| @article{wang2026s2r, |
| title = {From Synthesis to Removal: Physics-Grounded Reflection Simulation and Diffusion-Based Video Dereflection}, |
| author = {Wang, Zepeng and Hu, Jiagao and Li, Fuhao and Chen, Yuxuan and Wang, Fei and Zhou, Daiguo}, |
| journal = {arXiv preprint arXiv:2608.11562}, |
| year = {2026} |
| } |
| ``` |
|
|
