Introducing 🇨🇭WindowSeat🇨🇭 –– our new method for removing reflections from photos taken through windows, on planes, in malls, offices, and other glass-filled environments. 
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Introducing 🇨🇭WindowSeat🇨🇭 –– our new method for removing reflections from photos taken through windows, on planes, in malls, offices, and other glass-filled environments. 
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Finetuning a foundation diffusion transformer for reflection removal quickly runs up against the limits of what existing datasets and techniques can offer. To fill that gap, we generate physically accurate examples in Blender that simulate realistic glass and reflection effects. This data enables strong performance on both established benchmarks and previously unseen images.
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Finetuning a foundation diffusion transformer for reflection removal quickly runs up against the limits of what existing datasets and techniques can offer. To fill that gap, we generate physically accurate examples in Blender that simulate realistic glass and reflection effects. This data enables strong performance on both established benchmarks and previously unseen images.
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To make this practical, the open-source Apache-2 model builds on Qwen-Image-Edit-2509, a 20B image-editing diffusion transformer that runs on a single GPU and can be fine-tuned in about a day. WindowSeat keeps its use of the underlying DiT cleanly separated from the data and training recipe, allowing future advances in base models to be incorporated with minimal friction.
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To make this practical, the open-source Apache-2 model builds on Qwen-Image-Edit-2509, a 20B image-editing diffusion transformer that runs on a single GPU and can be fine-tuned in about a day. WindowSeat keeps its use of the underlying DiT cleanly separated from the data and training recipe, allowing future advances in base models to be incorporated with minimal friction.
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Try it out with your own photos in this interactive demo: 
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Try it out with your own photos in this interactive demo: 
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🤗 
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🤗 
https://huggingface.co/spaces/toshas/windowseat-reflection-removal
toshas/windowseat-reflection-removal
space
resource
https://huggingface.co/spaces/toshas/windowseat-reflection-removal
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Other resources:
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Other resources:
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🌎 Website: 
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🌎 Website: 
https://huggingface.co/spaces/huawei-bayerlab/windowseat-reflection-removal-web
huawei-bayerlab/windowseat-reflection-removal-web
space
resource
https://huggingface.co/spaces/huawei-bayerlab/windowseat-reflection-removal-web
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🎓 Paper: 
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🎓 Paper: 
Reflection Removal through Efficient Adaptation of Diffusion Transformers (2512.05000)
https://huggingface.co/papers/2512.05000
2512.05000
paper
resource
https://huggingface.co/papers/2512.05000
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🤗 Model: 
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🤗 Model: 
https://huggingface.co/huawei-bayerlab/windowseat-reflection-removal-v1-0
huawei-bayerlab/windowseat-reflection-removal-v1-0
model
resource
https://huggingface.co/huawei-bayerlab/windowseat-reflection-removal-v1-0
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🐙 Code: 
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🐙 Code: 
https://github.com/huawei-bayerlab/windowseat-reflection-removal
https://github.com/huawei-bayerlab/windowseat-reflection-removal
link
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Team: Daniyar Zakarin (
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Team: Daniyar Zakarin (
@daniyarzt
mention
daniyarzt
)*, Thiemo Wandel (
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)*, Thiemo Wandel (
@thiemo-wandel
mention
thiemo-wandel
)*, Anton Obukhov (
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)*, Anton Obukhov (
@toshas
mention
toshas
), Dengxin Dai. 
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), Dengxin Dai. 
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*Work done during internships at HUAWEI Bayer Lab
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*Work done during internships at HUAWEI Bayer Lab
Introducing 🇨🇭WindowSeat🇨🇭 –– our new method for removing reflections from photos taken through windows, on planes, in malls, offices, and other glass-filled environments. 

Finetuning a foundation diffusion transformer for reflection removal quickly runs up against the limits of what existing datasets and techniques can offer. To fill that gap, we generate physically accurate examples in Blender that simulate realistic glass and reflection effects. This data enables strong performance on both established benchmarks and previously unseen images.

To make this practical, the open-source Apache-2 model builds on Qwen-Image-Edit-2509, a 20B image-editing diffusion transformer that runs on a single GPU and can be fine-tuned in about a day. WindowSeat keeps its use of the underlying DiT cleanly separated from the data and training recipe, allowing future advances in base models to be incorporated with minimal friction.

Try it out with your own photos in this interactive demo: 
🤗 https://huggingface.co/spaces/toshas/windowseat-reflection-removal

Other resources:
🌎 Website: https://huggingface.co/spaces/huawei-bayerlab/windowseat-reflection-removal-web
🎓 Paper: https://huggingface.co/papers/2512.05000
🤗 Model: https://huggingface.co/huawei-bayerlab/windowseat-reflection-removal-v1-0
🐙 Code: https://github.com/huawei-bayerlab/windowseat-reflection-removal

Team: Daniyar Zakarin (@daniyarzt)*, Thiemo Wandel (@thiemo-wandel)*, Anton Obukhov (@toshas), Dengxin Dai. 
*Work done during internships at HUAWEI Bayer Lab
🔥
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