datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
uninavid-objnav-demolibero_plus_object
libero_plus_object: detailed LeRobot v3.0
This dataset was converted from the LIBERO Plus LeRobot v2.1 libero_plus_object partition.
The original 8D state and 7D action vectors are preserved exactly as
raw_state.ref_state and raw_action.ref_action. Canonical low-dimensional fields follow
failure_rollout_data/dataset.md; debug.gripper_eef_* contains the ground-truth next-step
relative EEF motion for inspection.
Required camera transform for canonical training
The… See the full description on the dataset page: https://huggingface.co/datasets/typoverflow/libero_plus_object.E2E_real_object
E2E Real Object Direction
A video-based benchmark for evaluating VideoLLMs' directional reasoning and object recognition on real-world objects.
Conditions
Condition
Question
Answer
Purpose
direction_only
"In which direction is the object moving?"
"Up"
Baseline direction recognition
direction_obj_in_q
"In which direction is the car moving?"
"Up"
Does naming the object help?
direction_obj_in_a
"In which direction is the object moving?"
"The car is moving up"… See the full description on the dataset page: https://huggingface.co/datasets/KHUjongseo/E2E_real_object.libero_object_mj332
libero_object_no_noops_lerobot: detailed LeRobot v3.0
This dataset was converted from the Fast-WAM LIBERO MuJoCo 3.3.2 LeRobot v2.1
libero_object_no_noops_lerobot partition. It contains successful demonstrations whose historical no-op actions
were removed by simulator replay before this conversion. This converter preserves all remaining
frames and does not apply any additional filtering.
The original 8D state and 7D action vectors are preserved exactly as
raw_state.ref_state and… See the full description on the dataset page: https://huggingface.co/datasets/typoverflow/libero_object_mj332.