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MultiHOIEdit

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The dataset generation failed

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
height: int64
width: int64
num_interactions: int64
source_prompt: string
box_labels: list<item: string>
  child 0, item: string
hoi_labels: list<item: string>
  child 0, item: string
hoi_results: list<item: struct<objects: string, verbs: string, boxes_h: list<item: double>, boxes_o: list<item: d (... 8 chars omitted)
  child 0, item: struct<objects: string, verbs: string, boxes_h: list<item: double>, boxes_o: list<item: double>>
      child 0, objects: string
      child 1, verbs: string
      child 2, boxes_h: list<item: double>
          child 0, item: double
      child 3, boxes_o: list<item: double>
          child 0, item: double
scene: string
to
{'Bs': List(Value('float64')), 'Bo': List(Value('float64')), 'meta': {'regime': Value('string'), 'energy': Value('float64'), 'lambdas': List(Value('float64')), 'key': List(Value('int64'))}, 'H': Value('int64'), 'W': Value('int64'), 'verb': Value('string'), 'object': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 764, in write_table
                  self.write_rows_on_file()  # in case there are buffered rows to write first
                  ~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 663, in write_rows_on_file
                  self._write_table(table)
                  ~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              height: int64
              width: int64
              num_interactions: int64
              source_prompt: string
              box_labels: list<item: string>
                child 0, item: string
              hoi_labels: list<item: string>
                child 0, item: string
              hoi_results: list<item: struct<objects: string, verbs: string, boxes_h: list<item: double>, boxes_o: list<item: d (... 8 chars omitted)
                child 0, item: struct<objects: string, verbs: string, boxes_h: list<item: double>, boxes_o: list<item: double>>
                    child 0, objects: string
                    child 1, verbs: string
                    child 2, boxes_h: list<item: double>
                        child 0, item: double
                    child 3, boxes_o: list<item: double>
                        child 0, item: double
              scene: string
              to
              {'Bs': List(Value('float64')), 'Bo': List(Value('float64')), 'meta': {'regime': Value('string'), 'energy': Value('float64'), 'lambdas': List(Value('float64')), 'key': List(Value('int64'))}, 'H': Value('int64'), 'W': Value('int64'), 'verb': Value('string'), 'object': Value('string')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 8 new columns ({'hoi_labels', 'source_prompt', 'hoi_results', 'scene', 'box_labels', 'width', 'num_interactions', 'height'}) and 7 missing columns ({'object', 'meta', 'verb', 'Bo', 'W', 'H', 'Bs'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/jiuntian/MultiHOIEdit/0406fe95-4784-47d5-9661-983efc68ddc5/edits/target_boxes_000.json (at revision 4dffc6f30458af7102abca0331706233d94c07a1), ['hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/00928c72-cf18-4a8f-8bd1-40961bdbc922/edits/target_boxes_000.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/00928c72-cf18-4a8f-8bd1-40961bdbc922/edits/target_boxes_001.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/00928c72-cf18-4a8f-8bd1-40961bdbc922/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/0406fe95-4784-47d5-9661-983efc68ddc5/edits/target_boxes_000.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/0406fe95-4784-47d5-9661-983efc68ddc5/edits/target_boxes_001.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/0406fe95-4784-47d5-9661-983efc68ddc5/edits/target_boxes_002.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/0406fe95-4784-47d5-9661-983efc68ddc5/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/060cd24f-7c6c-49f8-8715-b88cd74bdfbe/edits/target_boxes_000.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/060cd24f-7c6c-49f8-8715-b88cd74bdfbe/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/0778caae-23d6-4c75-92bc-85ec3a932e03/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/07971065-d35e-4126-9a7a-53b83b1fe0a2/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/085892e8-e790-41c4-8ad0-3e67577b7664/metadata.json', 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'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/dbbc22e5-9a22-4f88-97cf-c9d3ce2e5a4e/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/de45d83d-024d-4c37-a16c-df366521cff6/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/df173212-f519-4b5e-b251-2782e6955027/edits/target_boxes_000.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/df173212-f519-4b5e-b251-2782e6955027/edits/target_boxes_001.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/df173212-f519-4b5e-b251-2782e6955027/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/dfa6d767-df84-462e-b5a4-201ee8a64df8/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/dfc09e79-6358-4c01-9213-5e1418952b61/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/dfd560f6-c6b3-422b-af99-22873cbc8027/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e0da1587-3d6c-44f1-8590-5c952d144f36/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e2b3ffc5-7d4b-46d1-8a4c-b88992bc4cbf/edits/target_boxes_000.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e2b3ffc5-7d4b-46d1-8a4c-b88992bc4cbf/edits/target_boxes_001.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e2b3ffc5-7d4b-46d1-8a4c-b88992bc4cbf/edits/target_boxes_002.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e2b3ffc5-7d4b-46d1-8a4c-b88992bc4cbf/edits/target_boxes_003.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e2b3ffc5-7d4b-46d1-8a4c-b88992bc4cbf/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e305a537-5798-4659-8017-5954f737311b/edits/target_boxes_000.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e305a537-5798-4659-8017-5954f737311b/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e4f11dc3-ba09-4e52-8b2e-52179f0de413/edits/target_boxes_000.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e4f11dc3-ba09-4e52-8b2e-52179f0de413/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e51cac93-3723-4e53-bc48-18025e75ad9c/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e59560d3-b1be-4408-b426-b0f346573cb4/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e5a280ad-9182-4eee-ba97-87d9431bbe11/edits/target_boxes_000.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e5a280ad-9182-4eee-ba97-87d9431bbe11/edits/target_boxes_001.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e5a280ad-9182-4eee-ba97-87d9431bbe11/edits/target_boxes_002.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e5a280ad-9182-4eee-ba97-87d9431bbe11/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e652f575-1f93-4475-96c6-070457ea07c5/edits/target_boxes_000.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e652f575-1f93-4475-96c6-070457ea07c5/edits/target_boxes_001.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e652f575-1f93-4475-96c6-070457ea07c5/edits/target_boxes_002.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e652f575-1f93-4475-96c6-070457ea07c5/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e7fc2d16-251c-4b60-b933-0435f8334a2c/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e8675025-9469-42ea-8045-c2072ae3c0e1/edits/target_boxes_000.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e8675025-9469-42ea-8045-c2072ae3c0e1/edits/target_boxes_001.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/e8675025-9469-42ea-8045-c2072ae3c0e1/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/eb65e049-722d-4fc6-b19d-18bd2fa6ff7f/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/ed00abc0-f60e-4ae8-b463-6d3e80db2327/edits/target_boxes_000.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/ed00abc0-f60e-4ae8-b463-6d3e80db2327/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/edit_infos.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/ee10f7ad-56e9-4703-9a5d-8518b27cf619/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/ee21fabe-3d1a-448d-8a66-8fd7dce1a8de/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/ef551acd-485a-478d-8de9-6cec6bf715f2/edits/target_boxes_000.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/ef551acd-485a-478d-8de9-6cec6bf715f2/edits/target_boxes_001.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/ef551acd-485a-478d-8de9-6cec6bf715f2/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/f2f68295-f0e1-4532-88f2-09167e3a5697/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/f7b808de-7582-4c84-8bce-a9f30c52f700/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/f8541a99-fcf3-417f-8160-4a91d7e1ae86/edits/target_boxes_000.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/f8541a99-fcf3-417f-8160-4a91d7e1ae86/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/f8e1a15c-e873-4499-a65e-580c6936f966/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/f9a3fd4c-e4aa-4988-b6d8-c63213f01e62/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/f9aa573f-1444-41b8-bfcf-da3f0d38778a/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/fc40545a-49d8-4850-8546-35bda2dd500b/edits/target_boxes_000.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/fc40545a-49d8-4850-8546-35bda2dd500b/edits/target_boxes_001.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/fc40545a-49d8-4850-8546-35bda2dd500b/edits/target_boxes_002.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/fc40545a-49d8-4850-8546-35bda2dd500b/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/ff0534d6-f2ff-4153-adf9-a4898deb6736/edits/target_boxes_000.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/ff0534d6-f2ff-4153-adf9-a4898deb6736/metadata.json', 'hf://datasets/jiuntian/MultiHOIEdit@4dffc6f30458af7102abca0331706233d94c07a1/ffbefb1a-4bae-493d-b2fb-e980f1bd0659/metadata.json']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1858, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                                            ~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 781, in finalize
                  self.write_rows_on_file()
                  ~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 663, in write_rows_on_file
                  self._write_table(table)
                  ~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              height: int64
              width: int64
              num_interactions: int64
              source_prompt: string
              box_labels: list<item: string>
                child 0, item: string
              hoi_labels: list<item: string>
                child 0, item: string
              hoi_results: list<item: struct<objects: string, verbs: string, boxes_h: list<item: double>, boxes_o: list<item: d (... 8 chars omitted)
                child 0, item: struct<objects: string, verbs: string, boxes_h: list<item: double>, boxes_o: list<item: double>>
                    child 0, objects: string
                    child 1, verbs: string
                    child 2, boxes_h: list<item: double>
                        child 0, item: double
                    child 3, boxes_o: list<item: double>
                        child 0, item: double
              scene: string
              to
              {'Bs': List(Value('float64')), 'Bo': List(Value('float64')), 'meta': {'regime': Value('string'), 'energy': Value('float64'), 'lambdas': List(Value('float64')), 'key': List(Value('int64'))}, 'H': Value('int64'), 'W': Value('int64'), 'verb': Value('string'), 'object': Value('string')}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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.

Bs list	Bo list	meta dict	H int64	W int64	verb string	object string
[ 0.5470549038, 0.1815640678, 0.859644268, 0.8670429937 ]	[ 0.5641768457, 0.1570266872, 0.9587073256, 0.749588047 ]	{ "regime": "A", "energy": -0.2918758516, "lambdas": [ 0.5803559179, 0.4196440541 ], "key": [ 8, 30 ] }	1,333	753	carry	skis
[ 0.2424961207, 0.1757215312, 0.5313748667, 0.8185284236 ]	[ 0.1100794069, 0.3177811207, 0.6741037153, 0.6943947748 ]	{ "regime": "A", "energy": -0.5366738798, "lambdas": [ 0.54418903, 0.4558109439 ], "key": [ 8, 31 ] }	1,333	753	carry	snowboard
[ 0.2424961207, 0.1757215312, 0.5313748667, 0.8185284236 ]	[ 0.001336289, 0.6574042192, 0.8677823699, 0.9249380216 ]	{ "regime": "A", "energy": -0.4904721552, "lambdas": [ 0.5684925059, 0.431507466 ], "key": [ 93, 31 ] }	1,333	753	stand_on	snowboard
[ 0.5470549038, 0.1815640678, 0.859644268, 0.8670429937 ]	[ 0.4042454855, 0.2339486468, 0.8153220452, 0.8550669161 ]	{ "regime": "A", "energy": -0.395018233, "lambdas": [ 0.5676150346, 0.4323849353 ], "key": [ 36, 30 ] }	1,333	753	hold	skis
[ 0.2424961207, 0.1757215312, 0.5313748667, 0.8185284236 ]	[ 0, 0.6663354987, 0.9896687663, 0.8901602537 ]	{ "regime": "A", "energy": -0.496966396, "lambdas": [ 0.5665783418, 0.43342164 ], "key": [ 32, 31 ] }	1,333	753	grind	snowboard
[ 0.2424961207, 0.1757215312, 0.5313748667, 0.8185284236 ]	[ 0.0463627667, 0.550774336, 0.9599970885, 0.8727965988 ]	{ "regime": "A", "energy": -0.4697825581, "lambdas": [ 0.5500011099, 0.4499988646 ], "key": [ 43, 31 ] }	1,333	753	jump	snowboard
null	null	null	null	null	null	null
[ 0.3434820726, 0.1343961313, 0.6250374544, 0.9153208131 ]	[ 0.3979136416, 0.7147776083, 0.505020588, 0.8970219383 ]	{ "regime": "A", "energy": -0.6396433211, "lambdas": [ 0.6754970951, 0.3245028812 ], "key": [ 67, 32 ] }	753	1,333	pick_up	sports_ball
[ 0.3434820726, 0.1343961313, 0.6250374544, 0.9153208131 ]	[ 0.4229379641, 0.4178808853, 0.5268722271, 0.6104626903 ]	{ "regime": "A", "energy": -0.7188250964, "lambdas": [ 0.6288551429, 0.3711448315 ], "key": [ 36, 35 ] }	753	1,333	hold	baseball_glove
[ 0.3434820726, 0.1343961313, 0.6250374544, 0.9153208131 ]	[ 0.3603402987, 0.7691391011, 0.440502948, 0.9093578486 ]	{ "regime": "A", "energy": -0.7055862051, "lambdas": [ 0.6779215155, 0.3220784514 ], "key": [ 41, 32 ] }	753	1,333	inspect	sports_ball
[ 0.3434820726, 0.1343961313, 0.6250374544, 0.9153208131 ]	[ 0.4815984727, 0.4162910938, 0.5753958173, 0.5900901197 ]	{ "regime": "A", "energy": -0.7123291545, "lambdas": [ 0.6288551429, 0.3711448315 ], "key": [ 36, 35 ] }	753	1,333	hold	baseball_glove
[ 0.3434820726, 0.1343961313, 0.6250374544, 0.9153208131 ]	[ 0.4521238952, 0.6255100853, 0.5278138993, 0.7544442186 ]	{ "regime": "A", "energy": -0.7272207792, "lambdas": [ 0.6711555537, 0.3288444211 ], "key": [ 44, 32 ] }	753	1,333	kick	sports_ball
[ 0.3434820726, 0.1343961313, 0.6250374544, 0.9153208131 ]	[ 0.4333856902, 0.3895562363, 0.5290959123, 0.5668996783 ]	{ "regime": "A", "energy": -0.7112122642, "lambdas": [ 0.6288551429, 0.3711448315 ], "key": [ 36, 35 ] }	753	1,333	hold	baseball_glove
null	null	null	null	null	null	null
[ 0.005375296, 0.010956913, 0.9933700258, 0.987261647 ]	[ 0.3787830854, 0.5234418956, 0.8445703676, 0.7503821451 ]	{ "regime": "A", "energy": -0.5908150947, "lambdas": [ 0.5061755557, 0.493824424 ], "key": [ 89, 41 ] }	1,333	753	smell	cup
[ 0.005375296, 0.010956913, 0.9933700258, 0.987261647 ]	[ 0.2680430621, 0.3773262499, 0.7535205856, 0.6380808917 ]	{ "regime": "A", "energy": -0.5621015812, "lambdas": [ 0.63618157, 0.363818405 ], "key": [ 50, 42 ] }	1,333	753	lift	fork
null	null	null	null	null	null	null
null	null	null	null	null	null	null
null	null	null	null	null	null	null
null	null	null	null	null	null	null
null	null	null	null	null	null	null
[ 0.1064745231, 0.1154218074, 0.8817806573, 0.992365523 ]	[ 0.657448737, 0.6858026457, 0.9464261282, 0.8464686057 ]	{ "regime": "A", "energy": -0.7106647502, "lambdas": [ 0.7438431419, 0.2561568287 ], "key": [ 19, 32 ] }	1,333	753	dribble	sports_ball
[ 0.1064745231, 0.1154218074, 0.8817806573, 0.992365523 ]	[ 0, 0.2066059728, 0.2850163879, 0.3192125622 ]	{ "regime": "A", "energy": -0.6641255006, "lambdas": [ 0.6981020851, 0.3018978926 ], "key": [ 9, 29 ] }	1,333	753	catch	frisbee
null	null	null	null	null	null	null
null	null	null	null	null	null	null
[ 0.693574117, 0.2977404976, 0.8973939006, 0.8605539703 ]	[ 0.4661095174, 0.6255226517, 0.9991666667, 0.99875 ]	{ "regime": "A", "energy": 0.3859934678, "lambdas": [ 0.4219135809, 0.578086393 ], "key": [ 40, 21 ] }	800	1,200	hunt	bear
[ 0.6780041504, 0.1662425995, 0.9129638672, 0.9920518494 ]	[ 0.5138183594, 0.2588489532, 0.6337017822, 0.4386740875 ]	{ "regime": "A", "energy": -0.6170921008, "lambdas": [ 0.7820047868, 0.2179951891 ], "key": [ 10, 14 ] }	800	1,200	chase	bird
null	null	null	null	null	null	null
[ 0.4315036011, 0.2358197784, 0.7293547058, 0.7799347432 ]	[ 0.1650626755, 0.5050650024, 0.9162971497, 0.8095777384 ]	{ "regime": "A", "energy": -0.6041222825, "lambdas": [ 0.5964891526, 0.4035108262 ], "key": [ 0, 31 ] }	1,200	800	adjust	snowboard
[ 0.4315036011, 0.2358197784, 0.7293547058, 0.7799347432 ]	[ 0.1645941353, 0.5836787415, 0.99875, 0.8830186971 ]	{ "regime": "A", "energy": -0.5391397985, "lambdas": [ 0.5623760445, 0.437623927 ], "key": [ 76, 31 ] }	1,200	800	ride	snowboard
[ 0.4315036011, 0.2358197784, 0.7293547058, 0.7799347432 ]	[ 0.1203588486, 0.5406746928, 0.905178833, 0.8588012695 ]	{ "regime": "A", "energy": -0.6640342311, "lambdas": [ 0.5964891526, 0.4035108262 ], "key": [ 0, 31 ] }	1,200	800	adjust	snowboard
[ 0.4315036011, 0.2358197784, 0.7293547058, 0.7799347432 ]	[ 0.2276275635, 0.6266487122, 0.9606243134, 0.8815033976 ]	{ "regime": "A", "energy": -0.5606203568, "lambdas": [ 0.5684925059, 0.431507466 ], "key": [ 93, 31 ] }	1,200	800	stand_on	snowboard
[ 0.4315036011, 0.2358197784, 0.7293547058, 0.7799347432 ]	[ 0.2339612961, 0.5844937642, 0.9272012329, 0.8255253601 ]	{ "regime": "A", "energy": -0.5893602199, "lambdas": [ 0.5684925059, 0.431507466 ], "key": [ 93, 31 ] }	1,200	800	stand_on	snowboard
[ 0.4315036011, 0.2358197784, 0.7293547058, 0.7799347432 ]	[ 0.2622870064, 0.6710760498, 0.9103066254, 0.8318251038 ]	{ "regime": "A", "energy": -0.6151512617, "lambdas": [ 0.5665783418, 0.43342164 ], "key": [ 32, 31 ] }	1,200	800	grind	snowboard
null	null	null	null	null	null	null
null	null	null	null	null	null	null
null	null	null	null	null	null	null
null	null	null	null	null	null	null
null	null	null	null	null	null	null
[ 0.0576573753, 0.105276915, 0.4466040039, 0.9665113156 ]	[ 0.1284334946, 0.1685498496, 0.6361491776, 0.7029035246 ]	{ "regime": "A", "energy": -0.497678037, "lambdas": [ 0.5557493094, 0.4442506603 ], "key": [ 36, 24 ] }	1,061	800	hold	backpack
[ 0.0576573753, 0.105276915, 0.4466040039, 0.9665113156 ]	[ 0.152727766, 0.4751499474, 0.6718370819, 0.9599775625 ]	{ "regime": "A", "energy": -0.4773527255, "lambdas": [ 0.5014496098, 0.4985503742 ], "key": [ 41, 24 ] }	1,061	800	inspect	backpack
[ 0.4108680725, 0.1220687881, 0.677831192, 0.7790315648 ]	[ 0.1757928085, 0.4832168277, 0.898035202, 0.9990574929 ]	{ "regime": "A", "energy": -0.6048292617, "lambdas": [ 0.4674877666, 0.5325122198 ], "key": [ 58, 28 ] }	1,061	800	open	suitcase
null	null	null	null	null	null	null
[ 0.2185590422, 0.105350647, 0.700547257, 0.9915091705 ]	[ 0.3624497395, 0.2989061546, 0.5437423605, 0.655419693 ]	{ "regime": "A", "energy": -0.7203741931, "lambdas": [ 0.6478913129, 0.3521086665 ], "key": [ 36, 39 ] }	800	1,061	hold	bottle
[ 0.2185590422, 0.105350647, 0.700547257, 0.9915091705 ]	[ 0.4797120521, 0.5767578506, 0.6031547065, 0.7529096222 ]	{ "regime": "A", "energy": -0.7156275018, "lambdas": [ 0.6177018921, 0.3822980845 ], "key": [ 36, 41 ] }	800	1,061	hold	cup
[ 0.2185590422, 0.105350647, 0.700547257, 0.9915091705 ]	[ 0.3512844765, 0.3691015625, 0.5235262627, 0.7078165436 ]	{ "regime": "A", "energy": -0.6816618885, "lambdas": [ 0.6478913129, 0.3521086665 ], "key": [ 36, 39 ] }	800	1,061	hold	bottle
[ 0.2185590422, 0.105350647, 0.700547257, 0.9915091705 ]	[ 0.4167014508, 0.3538496399, 0.5798560744, 0.573074646 ]	{ "regime": "A", "energy": -0.7513673587, "lambdas": [ 0.7188035438, 0.2811964395 ], "key": [ 20, 41 ] }	800	1,061	drink_with	cup
[ 0.2185590422, 0.105350647, 0.700547257, 0.9915091705 ]	[ 0.2402804534, 0.3953570557, 0.4883853722, 0.9120669556 ]	{ "regime": "A", "energy": -0.5400276881, "lambdas": [ 0.7350701453, 0.2649298428 ], "key": [ 48, 39 ] }	800	1,061	lick	bottle
[ 0.2185590422, 0.105350647, 0.700547257, 0.9915091705 ]	[ 0.4550088061, 0.627905426, 0.567930173, 0.8009114075 ]	{ "regime": "A", "energy": -0.6853100583, "lambdas": [ 0.5587205628, 0.4412794127 ], "key": [ 41, 41 ] }	800	1,061	inspect	cup
[ 0.2185590422, 0.105350647, 0.700547257, 0.9915091705 ]	[ 0.3872263312, 0.5449292755, 0.5288921216, 0.9102070618 ]	{ "regime": "A", "energy": -0.7099154784, "lambdas": [ 0.6624921949, 0.3375077797 ], "key": [ 58, 39 ] }	800	1,061	open	bottle
[ 0.2185590422, 0.105350647, 0.700547257, 0.9915091705 ]	[ 0.3689942212, 0.3884580612, 0.5201484472, 0.5889263535 ]	{ "regime": "A", "energy": -0.7672528036, "lambdas": [ 0.689870437, 0.3101295474 ], "key": [ 85, 41 ] }	800	1,061	sip	cup
null	null	null	null	null	null	null
null	null	null	null	null	null	null
[ 0.0061990319, 0.3021071048, 0.8865622309, 0.9912774214 ]	[ 0.144536164, 0.6930276423, 0.7939525265, 0.9160146177 ]	{ "regime": "A", "energy": -0.5574112046, "lambdas": [ 0.4207610117, 0.5792389569 ], "key": [ 111, 51 ] }	1,333	753	wash	carrot
[ 0.0061990319, 0.3021071048, 0.8865622309, 0.9912774214 ]	[ 0.2022230901, 0.5432389439, 0.9986719788, 0.9243028531 ]	{ "regime": "A", "energy": -0.6089494984, "lambdas": [ 0.6382869556, 0.3617130339 ], "key": [ 61, 75 ] }	1,333	753	paint	vase
null	null	null	null	null	null	null
[ 0.309153705, 0.1437461035, 0.6620118647, 0.8577043858 ]	[ 0.3873678869, 0, 0.9986719788, 0.2807645576 ]	{ "regime": "A", "energy": -0.4444344916, "lambdas": [ 0.6016480767, 0.3983519057 ], "key": [ 53, 25 ] }	1,333	753	lose	umbrella
[ 0.309153705, 0.1437461035, 0.6620118647, 0.8577043858 ]	[ 0, 0.6464510415, 0.8917816689, 0.8619267549 ]	{ "regime": "A", "energy": -0.5049892977, "lambdas": [ 0.5528856263, 0.4471143518 ], "key": [ 87, 36 ] }	1,333	753	sit_on	skateboard
[ 0.309153705, 0.1437461035, 0.6620118647, 0.8577043858 ]	[ 0, 0, 0.9986719788, 0.6040967181 ]	{ "regime": "A", "energy": -0.0782755493, "lambdas": [ 0.5034422726, 0.4965577042 ], "key": [ 82, 25 ] }	1,333	753	set	umbrella
[ 0.309153705, 0.1437461035, 0.6620118647, 0.8577043858 ]	[ 0.1319971173, 0.7315676575, 0.8509213472, 0.9672950464 ]	{ "regime": "A", "energy": -0.5402647066, "lambdas": [ 0.5719375112, 0.4280624637 ], "key": [ 93, 36 ] }	1,333	753	stand_on	skateboard
[ 0.309153705, 0.1437461035, 0.6620118647, 0.8577043858 ]	[ 0.2363770018, 0, 0.9986719788, 0.4046460987 ]	{ "regime": "A", "energy": -0.4121029191, "lambdas": [ 0.6016480767, 0.3983519057 ], "key": [ 53, 25 ] }	1,333	753	lose	umbrella
[ 0.309153705, 0.1437461035, 0.6620118647, 0.8577043858 ]	[ 0.1344152605, 0.7335539787, 0.8870009869, 0.9918501354 ]	{ "regime": "A", "energy": -0.542777556, "lambdas": [ 0.5732907474, 0.4267092278 ], "key": [ 76, 36 ] }	1,333	753	ride	skateboard
[ 0.309153705, 0.1437461035, 0.6620118647, 0.8577043858 ]	[ 0.1110768514, 0, 0.9499336638, 0.4232827921 ]	{ "regime": "A", "energy": -0.4412096294, "lambdas": [ 0.6016480767, 0.3983519057 ], "key": [ 53, 25 ] }	1,333	753	lose	umbrella
[ 0.309153705, 0.1437461035, 0.6620118647, 0.8577043858 ]	[ 0.1229281685, 0.7547547898, 0.8543851936, 0.9992498125 ]	{ "regime": "A", "energy": -0.5603091189, "lambdas": [ 0.5732907474, 0.4267092278 ], "key": [ 76, 36 ] }	1,333	753	ride	skateboard
null	null	null	null	null	null	null
[ 0.0219541796, 0.0029478073, 0.913874965, 0.9939334106 ]	[ 0.3269402507, 0.7313510132, 0.7290993995, 0.992980423 ]	{ "regime": "A", "energy": -0.4946236591, "lambdas": [ 0.6013575174, 0.3986424645 ], "key": [ 54, 55 ] }	800	1,061	make	cake
[ 0.0219541796, 0.0029478073, 0.913874965, 0.9939334106 ]	[ 0.3992525293, 0.511077652, 0.528214292, 0.6647197723 ]	{ "regime": "A", "energy": -0.6302627504, "lambdas": [ 0.8085818571, 0.1914181324 ], "key": [ 23, 50 ] }	800	1,061	eat	broccoli
[ 0.0219541904, 0.0029478073, 0.913874965, 0.9939334106 ]	[ 0.079951884, 0.5149918365, 0.9511755567, 0.99875 ]	{ "regime": "A", "energy": 0.3233330239, "lambdas": [ 0.2830588379, 0.7169411417 ], "key": [ 51, 55 ] }	800	1,061	light	cake
[ 0.0219541796, 0.0029478073, 0.913874965, 0.9939334106 ]	[ 0.5118787875, 0.5572758484, 0.6474683008, 0.7403125763 ]	{ "regime": "A", "energy": -0.6535481355, "lambdas": [ 0.5946500957, 0.4053498895 ], "key": [ 89, 50 ] }	800	1,061	smell	broccoli
[ 0.0219541796, 0.0029478073, 0.913874965, 0.9939334106 ]	[ 0.278384339, 0.7384493256, 0.6622594605, 0.99875 ]	{ "regime": "A", "energy": -0.3480463435, "lambdas": [ 0.5458275854, 0.4541723942 ], "key": [ 15, 55 ] }	800	1,061	cut	cake
[ 0.0219541796, 0.0029478073, 0.913874965, 0.9939334106 ]	[ 0.4536574037, 0.609442215, 0.5990511996, 0.7826610565 ]	{ "regime": "A", "energy": -0.6526764254, "lambdas": [ 0.8085818571, 0.1914181324 ], "key": [ 23, 50 ] }	800	1,061	eat	broccoli
[ 0.0219541796, 0.0029478073, 0.913874965, 0.9939334106 ]	[ 0.1680577284, 0.6514398956, 0.6003703298, 0.99875 ]	{ "regime": "A", "energy": -0.3565710441, "lambdas": [ 0.5458275854, 0.4541723942 ], "key": [ 15, 55 ] }	800	1,061	cut	cake
[ 0.0219541796, 0.0029478073, 0.913874965, 0.9939334106 ]	[ 0.5403234138, 0.4990431213, 0.6651102222, 0.6674969482 ]	{ "regime": "A", "energy": -0.659923353, "lambdas": [ 0.5946500957, 0.4053498895 ], "key": [ 89, 50 ] }	800	1,061	smell	broccoli
null	null	null	null	null	null	null
null	null	null	null	null	null	null
null	null	null	null	null	null	null
[ 0.3746753947, 0.1599631023, 0.5907088725, 0.8158837891 ]	[ 0.3145961253, 0.4869393539, 0.6809135437, 0.99875 ]	{ "regime": "A", "energy": -0.6166501943, "lambdas": [ 0.4674877666, 0.5325122198 ], "key": [ 58, 28 ] }	800	1,200	open	suitcase
[ 0.5673119609, 0.2164547729, 0.7027142843, 0.8893403625 ]	[ 0.4000277456, 0.1148503685, 0.7569856771, 0.6588314056 ]	{ "regime": "A", "energy": -0.6808286749, "lambdas": [ 0.7047433398, 0.2952566448 ], "key": [ 58, 25 ] }	800	1,200	open	umbrella
null	null	null	null	null	null	null
null	null	null	null	null	null	null
null	null	null	null	null	null	null
null	null	null	null	null	null	null
[ 0.544216156, 0.6204310608, 0.5978792826, 0.8627610016 ]	[ 0.4752679443, 0.7915077209, 0.5839649963, 0.9116921997 ]	{ "regime": "A", "energy": -0.5588216728, "lambdas": [ 0.4154653623, 0.5845346135 ], "key": [ 116, 28 ] }	800	1,200	zip	suitcase
[ 0.544216156, 0.6204310608, 0.5978792826, 0.8627610779 ]	[ 0, 0, 0.9991666667, 0.99875 ]	{ "regime": "A", "energy": 2.4404752976, "lambdas": [ 0.1645185869, 0.8354814021 ], "key": [ 4, 4 ] }	800	1,200	board	airplane
[ 0.544216156, 0.6204310608, 0.5978792826, 0.8627610016 ]	[ 0.4482171122, 0.6852387238, 0.6450999959, 0.9119704437 ]	{ "regime": "A", "energy": -0.2276954786, "lambdas": [ 0.4227035095, 0.5772964845 ], "key": [ 39, 28 ] }	800	1,200	hug	suitcase
[ 0.544216156, 0.6204310608, 0.5978792826, 0.8627610779 ]	[ 0, 0.1386261082, 0.9991666667, 0.9105210876 ]	{ "regime": "A", "energy": -0.4704869645, "lambdas": [ 0.1626539795, 0.8373460092 ], "key": [ 41, 4 ] }	800	1,200	inspect	airplane
null	null	null	null	null	null	null
[ 0.2137130483, 0.2361762619, 0.2783516693, 0.3565378571 ]	[ 0.0115837463, 0.1457457542, 0.5489146932, 0.6781014252 ]	{ "regime": "A", "energy": 0.2556261866, "lambdas": [ 0.251775069, 0.7482249175 ], "key": [ 76, 7 ] }	800	1,200	ride	truck
[ 0.6249245199, 0.2023518181, 0.8087651571, 0.7538737488 ]	[ 0.5348076884, 0.3038319588, 0.9190112305, 0.9311088562 ]	{ "regime": "B", "energy": -0.3610165662, "lambdas": [ 0.3724101878, 0.627589798 ], "key": [ 110, 3 ] }	800	1,200	walk	motorcycle
[ 0.3608579254, 0.2741826248, 0.4506132507, 0.5434486771 ]	[ 0.0183902089, 0.0322618198, 0.7458313497, 0.7404394531 ]	{ "regime": "B", "energy": -0.4815026961, "lambdas": [ 0.2104745363, 0.7895254465 ], "key": [ 17, 7 ] }	800	1,200	direct	truck
[ 0.6929064941, 0.1356661415, 0.8741137695, 0.6792880249 ]	[ 0.5348076884, 0.3038319588, 0.9190112305, 0.9311088562 ]	{ "regime": "B", "energy": -0.5788790524, "lambdas": [ 0.4443648587, 0.5556351269 ], "key": [ 43, 3 ] }	800	1,200	jump	motorcycle
[ 0.4129180145, 0.2725823212, 0.5593972778, 0.7120201874 ]	[ 0.0183902089, 0.0322618198, 0.7458313497, 0.7404394531 ]	{ "regime": "B", "energy": -0.6873101271, "lambdas": [ 0.3236295396, 0.6763704397 ], "key": [ 75, 7 ] }	800	1,200	repair	truck
[ 0.5179803975, 0, 0.8181480916, 0.7321308899 ]	[ 0.5348076884, 0.3038319588, 0.9190112305, 0.9311088562 ]	{ "regime": "B", "energy": 0.1907471764, "lambdas": [ 0.3062322379, 0.6937677544 ], "key": [ 37, 3 ] }	800	1,200	hop_on	motorcycle
null	null	null	null	null	null	null
[ 0.676394399, 0.4080007172, 0.9122741699, 0.9927325439 ]	[ 0.7348476664, 0.6574285126, 0.8150219727, 0.7776899719 ]	{ "regime": "A", "energy": -0.6839095027, "lambdas": [ 0.6121314239, 0.3878685539 ], "key": [ 41, 47 ] }	800	1,200	inspect	apple
[ 0.0033586919, 0.1541926003, 0.5684580994, 0.9927321625 ]	[ 0.2882971954, 0.005011605, 0.4455311076, 0.2060668755 ]	{ "regime": "A", "energy": -0.6699522188, "lambdas": [ 0.518133648, 0.4818663255 ], "key": [ 74, 14 ] }	800	1,200	release	bird
[ 0.676394399, 0.4080007172, 0.9122741699, 0.9927325439 ]	[ 0.7506607564, 0.5272076797, 0.8263008118, 0.6351296997 ]	{ "regime": "A", "energy": -0.6901786378, "lambdas": [ 0.6444474159, 0.3555525612 ], "key": [ 66, 47 ] }	800	1,200	pick	apple
[ 0.0033586919, 0.1541926003, 0.5684580994, 0.9927321625 ]	[ 0.075135924, 0.6177891159, 0.1799167887, 0.7684116364 ]	{ "regime": "A", "energy": -0.5566672137, "lambdas": [ 0.6245068218, 0.3754931421 ], "key": [ 112, 14 ] }	800	1,200	watch	bird
null	null	null	null	null	null	null
null	null	null	null	null	null	null

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Multi-HOI-Edit: Multiple Human-Object Interaction Editing

OneHOI Project Page | Paper (CVPR 2026)

Multi-HOI-Edit is the first benchmark for multiple human-object interaction editing task.

Citation

If you find this dataset useful for your research in HOI editing or image generation, please cite our CVPR 2026 paper:

@inproceedings{hoe2026onehoi,
  title={OneHOI: Unifying Human-Object Interaction Generation and Editing},
  author={Hoe, Jiun Tian and Hu, Weipeng and Jiang, Xudong and Tan, Yap-Peng and Chan, Chee Seng},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2026}
}
@misc{hoe2025interactedit,
    title={InteractEdit: Zero-Shot Editing of Human-Object Interactions in Images}, 
    author={Jiun Tian Hoe and Weipeng Hu and Wei Zhou and Chao Xie and Ziwei Wang and Chee Seng Chan and Xudong Jiang and Yap-Peng Tan},
    year={2025},
    eprint={2503.09130},
    archivePrefix={arXiv},
    primaryClass={cs.GR},
    url={https://arxiv.org/abs/2503.09130}, 
}

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Papers for jiuntian/MultiHOIEdit

OneHOI: Unifying Human-Object Interaction Generation and Editing

Paper • 2604.14062 • Published Apr 15 • 8

InteractEdit: Zero-Shot Editing of Human-Object Interactions in Images

Paper • 2503.09130 • Published Mar 12, 2025 • 1