Search is not available for this dataset
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The info cannot be fetched for the config 'default' of the dataset.
Error code: InfoError
Exception: FileNotFoundError
Message: Couldn't find any data file at /src/services/worker/EPFL-VILAB/TST-Scannet-pp. Couldn't find 'EPFL-VILAB/TST-Scannet-pp' on the Hugging Face Hub either: LocalEntryNotFoundError: An error happened while trying to locate the file on the Hub and we cannot find the requested files in the local cache. Please check your connection and try again or make sure your Internet connection is on.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 223, in compute_first_rows_from_streaming_response
info = get_dataset_config_info(path=dataset, config_name=config, token=hf_token)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 268, in get_dataset_config_info
builder = load_dataset_builder(
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1315, in load_dataset_builder
dataset_module = dataset_module_factory(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1203, in dataset_module_factory
raise FileNotFoundError(
FileNotFoundError: Couldn't find any data file at /src/services/worker/EPFL-VILAB/TST-Scannet-pp. Couldn't find 'EPFL-VILAB/TST-Scannet-pp' on the Hugging Face Hub either: LocalEntryNotFoundError: An error happened while trying to locate the file on the Hub and we cannot find the requested files in the local cache. Please check your connection and try again or make sure your Internet connection is on.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.
Dataset Card for TST-Scannet++
Dataset Summary
This custom TST-Scannet++ dataset is used in research work "Multimodality as Supervision: Self-Supervised Specialization to the Test Environment via Multimodality".
pretrain/is a multimodal pretraining dataset modified from the original ScanNet++ 3D dataset. It contains the 9 annotated tokenized modalities.
Dataset Structure Pretraining Data
TST-Scannet-pp/
├── pretrain/
│ ├── dslr/
│ │ ├── crop_settings/ # Contains .tar shards
│ │ ├── det/ # Contains .tar shards
│ │ ├── tok_canny_edge@224/ # Contains .tar shards
│ │ ├── ... # More tokenized feature directories
│ │ └── tok_semseg@224/ # Contains .tar shards
│ ├── iphone/
│ │ ├── crop_settings/ # Contains .tar shards
│ │ ├── det/ # Contains .tar shards
│ │ ├── tok_canny_edge@224/ # Contains .tar shards
│ │ ├── ... # More tokenized feature directories
│ │ └── tok_semseg@224/ # Contains .tar shards
│ └── transfer/
│ ├── crop_settings/ # Contains .tar shards
│ ├── det/ # Contains .tar shards
│ ├── tok_canny_edge@224/ # Contains .tar shards
│ ├── ... # More tokenized feature directories
│ └── tok_semseg@224/ # Contains .tar shards
└── README.md
Dataset Creation
We use ScanNet++, which is a large-scale dataset of real-world indoor spaces containing sub-millimeter resolution scans, paired with DSLR and iPhone RGB images. We use 8 scenes as the test space, and use a mix of iPhone and DSLR images from these scenes for pre-training. For generating the pretrain RGB images and the transfer/test sets please follow the instructions provided in the project repo.
Source Data
Original dataset samples are collected from ScanNet++ framework.
Citation Information
@inproceedings{singh2026tst,
title={Multimodality as Supervision: Self-Supervised Specialization to the Test Environment via Multimodality},
author={Kunal Pratap Singh and Ali Garjani and Rishubh Singh and Muhammad Uzair Khattak and Efe Tarhan and Jason Toskov and Andrei Atanov and O{\u{g}}uzhan Fatih Kar and Amir Zamir},
booktitle={International Conference on Learning Representations (ICLR)},
year={2026}
}
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