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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:    ValueError
Message:      Invalid string class label additional_real
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 2157, in _apply_feature_types_on_example
                  encoded_example = features.encode_example(example)
                                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2152, in encode_example
                  return encode_nested_example(self, example)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1437, in encode_nested_example
                  {k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1460, in encode_nested_example
                  return schema.encode_example(obj) if obj is not None else None
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1143, in encode_example
                  example_data = self.str2int(example_data)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1080, in str2int
                  output = [self._strval2int(value) for value in values]
                            ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1101, in _strval2int
                  raise ValueError(f"Invalid string class label {value}")
              ValueError: Invalid string class label additional_real

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GOR-IS Datasets

Project Page | Paper | GitHub

This repository contains the datasets for GOR-IS: 3D Gaussian Object Removal in the Intrinsic Space, presented as a Highlight at CVPR 2026.

We provide a comprehensive suite of datasets, including our proposed GOR-IS-Synthetic and GOR-IS-Real, along with additional real-world scenes (Additional-Real) sourced from Mip-NeRF 360 and Ref-Real, and synthetic scenes (Additional-Synthetic) featuring more complex inpainting textures. All datasets are fully preprocessed and contain the necessary components for our framework, enabling users to directly download, decompress, and use them without additional setup.

Dataset Organization

The organization of the datasets is as follows:

GOR-IS-datasets/
β”œβ”€β”€ gor-is-synthetic/
β”‚   β”œβ”€β”€ scene_1_colmap/
β”‚   β”‚   β”œβ”€β”€ images/ # input images
β”‚   β”‚   β”œβ”€β”€ object_mask/ # masks of target objects
β”‚   β”‚   β”œβ”€β”€ specular_mask/ # masks of specular regions
β”‚   β”‚   β”œβ”€β”€ sparse/ # COLMAP data
β”‚   β”‚   β”œβ”€β”€ normal/ # predicted normals
β”‚   β”‚   β”œβ”€β”€ train_list.txt
β”‚   β”‚   β”œβ”€β”€ val_list.txt
β”‚   β”‚   └── test_list.txt
β”‚   β”œβ”€β”€ scene_2_colmap/
β”‚   β”‚   └── ...
β”‚   └── ...
β”‚
β”œβ”€β”€ gor-is-real/
β”‚   β”œβ”€β”€ ...
β”‚
β”œβ”€β”€ additional-real/
β”‚   β”œβ”€β”€ ...
β”‚
β”œβ”€β”€ additional-synthetic/
β”‚   β”œβ”€β”€ ...

Citation

If you find our work is helpful, please consider citing:

@inproceedings{zhao2026gor-is,
  title={GOR-IS: 3D Gaussian Object Removal in the Intrinsic Space},
  author={Yonghao Zhao and Yupeng Gao and Jian Yang and Jin Xie and Beibei Wang},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2026}
}
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Paper for applezyh/GOR-IS-datasets