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Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation
🌼9Depth, surface normals, and albedo from a single image
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Marigold V2
🌼10Depth, surface normals, and albedo from a single image
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huawei-bayerlab/marigold-v2-0
Depth Estimation • Updated • 14 -
Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation
Paper • 2609.08084 • Published • 44
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Recent Activity
Papers
Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation
Reflection Removal through Efficient Adaptation of Diffusion Transformers
HUAWEI Bayer Lab
We use this space to contribute to the open-source community in the area of computer vision and computational photography.
The repositories only contain code of models, websites, and demonstrations for papers and are not official open-source products. For Huawei's major open source projects that are officially maintained, please refer to https://github.com/huawei and http://opensource.huawei.com/.
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WindowSeat Reflection Removal Project Page
🪟28Remove reflections from a single photo instantly
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WindowSeat Reflection Removal
🪟52Remove reflections from photos instantly
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huawei-bayerlab/windowseat-reflection-removal-v1-0
Image-to-Image • Updated • 46 -
Reflection Removal through Efficient Adaptation of Diffusion Transformers
Paper • 2512.05000 • Published • 18
-
Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation
🌼9Depth, surface normals, and albedo from a single image
-
Marigold V2
🌼10Depth, surface normals, and albedo from a single image
-
huawei-bayerlab/marigold-v2-0
Depth Estimation • Updated • 14 -
Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation
Paper • 2609.08084 • Published • 44
-
WindowSeat Reflection Removal Project Page
🪟28Remove reflections from a single photo instantly
-
WindowSeat Reflection Removal
🪟52Remove reflections from photos instantly
-
huawei-bayerlab/windowseat-reflection-removal-v1-0
Image-to-Image • Updated • 46 -
Reflection Removal through Efficient Adaptation of Diffusion Transformers
Paper • 2512.05000 • Published • 18