Zero-Shot Depth from Defocus
Paper • 2603.26658 • Published
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Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: UnidentifiedImageError
Message: cannot identify image file <_io.BytesIO object at 0x7fcd9c987f10>
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2240, in __iter__
example = _apply_feature_types_on_example(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2159, in _apply_feature_types_on_example
decoded_example = features.decode_example(encoded_example, token_per_repo_id=token_per_repo_id)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2204, in decode_example
column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1508, in decode_nested_example
return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/image.py", line 190, in decode_example
image = PIL.Image.open(bytes_)
^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/PIL/Image.py", line 3498, in open
raise UnidentifiedImageError(msg)
PIL.UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x7fcd9c987f10>Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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Zero-Shot Depth from Defocus
Yiming Zuo* · Hongyu Wen* · Venkat Subramanian* · Patrick Chen · Karhan Kayan · Mario Bijelic · Felix Heide · Jia Deng
(*Equal Contribution)
Princeton Vision & Learning Lab (PVL)
Paper · Project
Overview
We build the Infinigen Defocus synthetic dataset on top of Infinigen Indoors [33]. Infinigen is a procedural system for generating photorealistic indoor scenes. Owing to its procedural nature, it can produce unlimited variation at both the object and scene levels, yielding diverse shapes, layouts, and spatial compositions.
Infinigen uses Blender [8] for scene composition and rendering. Blender provides native support for camera aperture and focus distance, and supports synthesizing defocus effects during ray tracing using a thin-lens camera model [15]. This makes Blender suitable for generating realistic focus stacks with physically accurate defocus blur.
We modify the Infinigen generation pipeline so that, for each scene, it renders multiple images from the same camera pose while varying the aperture size and focus distance. We choose the rendering settings to match the distribution covered by \benchmarkname. Specifically, we render images using 5 aperture settings (F1.4/2.0/2.8/4.0/5.6), 9 focus distances (0.8/1.2/1.7/2.3/3.0/3.8/4.7/6.0/8.0m), and one additional all-in-focus image, resulting in 5 × 9 + 1 = 46 images per scene.
We use the rendered depth map of the all-in-focus image as the ground-truth depth. In total, we generate 500 scenes and manually reject the scenes with degenerated object layout or suboptimal camera placement, resulting in 200 scenes with the highest visual quality.
— Paper (arXiv)
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