license: cc-by-4.0
task_categories:
- other
size_categories:
- n<1K
dataset_info:
features:
- name: category
dtype: string
- name: path
dtype: string
- name: scale
dtype: float64
- name: rotation
dtype: float64
- name: 180-degree symmetry
dtype: int64
- name: 90-degree symmetry
dtype: int64
- name: round
dtype: int64
- name: rotation_red
dtype: 'null'
- name: rotation_green
dtype: 'null'
- name: mesh_extent_x
dtype: float64
- name: mesh_extent_y
dtype: float64
- name: mesh_extent_z
dtype: float64
- name: mesh_offset_x
dtype: float64
- name: mesh_offset_y
dtype: float64
- name: mesh_offset_z
dtype: float64
splits:
- name: all
num_bytes: 19039
num_examples: 109
download_size: 13548
dataset_size: 19039
configs:
- config_name: default
data_files:
- split: all
path: data/all-*
LychSim Objects Dataset
This dataset provides annotations for 3D assets used in LychSim, a controllable and interactive simulation framework for vision research.
For each 3D asset that appears in LychSim scenes, we annotate its semantic category, canonical scale, and pose alignment (the calibration yaw that puts the asset's "front" along +X), together with a precomputed mesh_offset so that spawning at location + mesh_offset lands the visual bounding box bottom-center exactly on the target location. These annotations are critical for producing semantically aligned ground-truth 3D object poses and for programmatic object placement and scene manipulation.
- Paper: LychSim: A Controllable and Interactive Simulation Framework for Vision Research
- Project Page: https://lychsim.github.io/
- Repository: https://github.com/wufeim/LychSim
Sample Usage
You can load this dataset using the Hugging Face datasets library:
from datasets import load_dataset
objects = load_dataset("wufeim/lychsim_objects")
License
This dataset is released under the Creative Commons Attribution 4.0 International license (CC BY 4.0).