# ObjectNet (Test set only)

Original paper: [ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models](https://objectnet.dev/objectnet-a-large-scale-bias-controlled-dataset-for-pushing-the-limits-of-object-recognition-models.pdf)

Homepage: https://objectnet.dev/

Bibtex:
```
@inproceedings{NEURIPS2019_97af07a1,
 author = {Barbu, Andrei and Mayo, David and Alverio, Julian and Luo, William and Wang, Christopher and Gutfreund, Dan and Tenenbaum, Josh and Katz, Boris},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models},
 url = {https://proceedings.neurips.cc/paper/2019/file/97af07a14cacba681feacf3012730892-Paper.pdf},
 volume = {32},
 year = {2019}
}
```
region:us
{}
TAGS
#region-us 

# ObjectNet (Test set only)

Original paper: ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models

Homepage: URL

Bibtex:

# ObjectNet (Test set only)

Original paper: ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models

Homepage: URL

Bibtex:
TAGS
#region-us 
 # ObjectNet (Test set only)

Original paper: ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models

Homepage: URL

Bibtex:
passage: TAGS
#region-us 
# ObjectNet (Test set only)

Original paper: ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models

Homepage: URL

Bibtex: