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| Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2605.05510 |
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| author | Seizinger, Tim Vasluianu, Florin-Alexandru Chen, Jeffrey Zhou, Zhuyun Wu, Zongwei Timofte, Radu Zhang, Dafeng Lin, Yipeng Yan, Qi Chen, Junhao Yang, Yang Singh, Divyavardhan Thacker, Hariom Mohammad, Hammad Maurya, Aanchal Upla, Kishor Raja, Kiran Zhou, Wei Huang, Hongyu Cho, Yujin Malivenko, Grigory Tu, Jiachen Shi, Yaokun Xu, Guoyi Jiang, Yaoxin Liu, Jiajia |
| author_facet | Seizinger, Tim Vasluianu, Florin-Alexandru Chen, Jeffrey Zhou, Zhuyun Wu, Zongwei Timofte, Radu Zhang, Dafeng Lin, Yipeng Yan, Qi Chen, Junhao Yang, Yang Singh, Divyavardhan Thacker, Hariom Mohammad, Hammad Maurya, Aanchal Upla, Kishor Raja, Kiran Zhou, Wei Huang, Hongyu Cho, Yujin Malivenko, Grigory Tu, Jiachen Shi, Yaokun Xu, Guoyi Jiang, Yaoxin Liu, Jiajia |
| contents | This study presents the outcomes of the first Controllable Bokeh Rendering Challenge at NTIRE and highlights the most effective submitted methodologies. In total, 44 participants registered for the competition, of which 8 teams submitted valid solutions after the conclusion of the final test phase. All submissions were evaluated on unseen images, focusing on portraits and intricate subjects with complex and visually appealing bokeh phenomena. In addition to the first track focusing on established quantitative fidelity metrics, we conducted a qualitative user study with a panel of experts for a second track focusing on perceptual assessment. As this was the inaugural challenge on this topic, most of the participants focused on refining and extending the Bokehlicious baseline method. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_05510 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | The First Controllable Bokeh Rendering Challenge at NTIRE 2026 Seizinger, Tim Vasluianu, Florin-Alexandru Chen, Jeffrey Zhou, Zhuyun Wu, Zongwei Timofte, Radu Zhang, Dafeng Lin, Yipeng Yan, Qi Chen, Junhao Yang, Yang Singh, Divyavardhan Thacker, Hariom Mohammad, Hammad Maurya, Aanchal Upla, Kishor Raja, Kiran Zhou, Wei Huang, Hongyu Cho, Yujin Malivenko, Grigory Tu, Jiachen Shi, Yaokun Xu, Guoyi Jiang, Yaoxin Liu, Jiajia Computer Vision and Pattern Recognition This study presents the outcomes of the first Controllable Bokeh Rendering Challenge at NTIRE and highlights the most effective submitted methodologies. In total, 44 participants registered for the competition, of which 8 teams submitted valid solutions after the conclusion of the final test phase. All submissions were evaluated on unseen images, focusing on portraits and intricate subjects with complex and visually appealing bokeh phenomena. In addition to the first track focusing on established quantitative fidelity metrics, we conducted a qualitative user study with a panel of experts for a second track focusing on perceptual assessment. As this was the inaugural challenge on this topic, most of the participants focused on refining and extending the Bokehlicious baseline method. |
| title | The First Controllable Bokeh Rendering Challenge at NTIRE 2026 |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2605.05510 |