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{
image_primary: ('batch', 'history_window', 256, 256, 3),
image_wrist: ('batch', 'history_window', 128, 128, 3),
}{
image_primary: ('batch', 256, 256, 3),
image_wrist: ('batch', 128, 128, 3),
language_instruction: {
attention_mask: ('batch', 16),
input_ids: ('batch', 16),
},
}| Dataset | Proportion of batch |
|---|---|
| Fractal (Brohan et al, 2022) | 17.0% |
| Kuka (Kalashnikov et al, 2018) | 17.0% |
| Bridge (Walke et al, 2023) | 17.0% |
| BC-Z (Jang et al, 2022) | 9.1% |
| Stanford Hydra Dataset (Belkhale et al, 2023) | 6.0% |
| Language Table~ (Lynch et al, 2023) | 5.9% |
| Taco Play (Rosete-Beas et al, 2022, Mees et al., 2023) | 3.6% |
| Furniture Bench Dataset (Heo et al, 2023) | 3.3% |
| UTAustin Mutex (Shah et al, 2023) | 3.0% |
| Austin Sailor Dataset (Nasiriany et al, 2022) | 2.9% |
| Roboturk (Mandlekar et al, 2018) | 2.8% |
| Toto (Zhou et al, 2023) | 2.4% |
| Austin Sirius Dataset (Liu et al, 2023) | 2.3% |
| Berkeley Autolab UR5 (Chen et al) | 1.5% |
| IAMLab CMU Pickup Insert (Saxena et al, 2023) | 1.2% |
| Viola (Zhu et al, 2023) | 1.2% |
| Berkeley Fanuc Manipulation (Zhu et al, 2023) | 1.0% |
| NYU Franka Play Dataset (Cui et al, 2022) | 0.9% |
| UCSD Kitchen Dataset (Ge Yan and Wang, 2023) | <0.1% |
| Jaco Play (Dass et al, 2023) | 0.6% |
| Berkeley Cable Routing (Luo et al, 2023) | 0.3% |
| Austin Buds Dataset (Zhu et al, 2022) | 0.3% |
| CMU Stretch (Mendonca et al, 2023) | 0.2% |
| NYU Door Opening (Pari et al, 2021) | 0.1% |
| DLR EDAN Shared Control (Quere et al, 2020) | 0.1% |