The dataset viewer is not available for this dataset.
Error code: ConfigNamesError
Exception: ReadTimeout
Message: (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: beb8e33d-9691-4bdb-83b9-940425c8106b)')
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 67, in compute_config_names_response
config_names = get_dataset_config_names(
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
dataset_module = dataset_module_factory(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1207, in dataset_module_factory
raise e1 from None
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1182, in dataset_module_factory
).get_module()
^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 598, in get_module
standalone_yaml_path = cached_path(
^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 180, in cached_path
).resolve_path(url_or_filename)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 198, in resolve_path
repo_and_revision_exist, err = self._repo_and_revision_exist(repo_type, repo_id, revision)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 125, in _repo_and_revision_exist
self._api.repo_info(
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_api.py", line 2816, in repo_info
return method(
^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_api.py", line 2673, in dataset_info
r = get_session().get(path, headers=headers, timeout=timeout, params=params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/requests/sessions.py", line 602, in get
return self.request("GET", url, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/requests/sessions.py", line 589, in request
resp = self.send(prep, **send_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/requests/sessions.py", line 703, in send
r = adapter.send(request, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/utils/_http.py", line 96, in send
return super().send(request, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/requests/adapters.py", line 690, in send
raise ReadTimeout(e, request=request)
requests.exceptions.ReadTimeout: (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: beb8e33d-9691-4bdb-83b9-940425c8106b)')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.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
MetricScenes
A metrically-grounded, in-the-wild dataset. For more details, please visit the project page.
Paper
Title: Honey, I Shrunk the Arc de Triomphe!
Authors: Yuanbo Xiangli, Hanyu Chen, Xueqing Tsang, Noah Snavely
Project page: https://metricscenes.github.io/
Abstract
Metric scale monocular geometry estimation has seen significant progress through large-scale data aggregation, yet current foundation models suffer from a persistent ''scale-collapse'' phenomenon: distant landmarks and vast landscapes are metrically underestimated. This performance gap stems from a training data bottleneck, where existing metric-scale datasets are hardware-constrained to unvaried street-level LiDAR or short-range indoor scans, or consist of synthetic data that lacks the semantic complexity of the physical world. To bridge this gap, we curate a new metrically-grounded, in-the-wild dataset that we call Metricscenes, gathered from a variety of sources including Internet photo collections and stereo imagery. We estimate camera poses and initial depth maps for each scene using off-the-shelf methods, and recover absolute scale from geo-tagged metadata as well as known stereo camera baselines. We also improve the quality of depth maps derived from MetricScenes via a new two-stage Poisson completion method. Fine-tuning MoGe-2 on our dataset significantly mitigates scale-collapse and achieves superior metric accuracy in unconstrained, open-domain scenes while maintaining state-of-the-art performance on standard benchmarks.
Release Structure
MetricScenes is aggregated from AerialMegaDepth, MegaScenes, and Stereo4D. We develop pipelines to extract metric-scale depth maps in each case. The public release is organized as dataset_name/scene_id/frame_id/...:
MetricScenes/
├── AerialMegaDepth/
│ ├── 0000
│ │ ├── 1000570923_c2a177031b_o
│ │ │ ├── depth_complete.png
│ │ │ ├── depth_partial.png
│ │ │ ├── image.jpg
│ │ │ └── meta.json
│ │ ├── 1001414672_f286cdb145_o
│ │ │ └── ...
│ │ └── ...
│ ├── 0001
│ │ └── ...
│ └── ...
├── MegaScenes/
│ ├── 000
│ │ ├── 000352
│ │ │ ├── depth_complete.png
│ │ │ ├── depth_partial.png
│ │ │ ├── image.jpg
│ │ │ └── meta.json
│ │ ├── 000373
│ │ │ └── ...
│ │ └── ...
│ ├── 001
│ │ └── ...
│ └── ...
├── Stereo4D/
│ ├── -3Sx43OYGJ8
│ │ ├── 15081748_f99
│ │ │ ├── depth_complete.png
│ │ │ ├── depth_partial.png
│ │ │ ├── image.jpg
│ │ │ └── meta.json
│ │ ├── 21755088_f99
│ │ │ └── ...
│ │ └── ...
│ ├── -5JaYFNtYlM
│ │ └── ...
│ └── ...
│
└── README.md
depth_partial.png is the incomplete depth from SfM/MVS or off-the-shelf geometric models; depth_complete.png is the completed depth using our proposed two-stage edge-aware Poisson completion method; image.jpg is the RGB image; meta.json contains camera parameters like intrinsics, extrinsics etc.
Licensing Metadata
The MetricScenes dataset is licensed under the Creative Commons Attribution 4.0 International License. The original images come with their own licenses.
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