Other

TLV (Touch-Language-Vision)

Touch-language-vision alignment

Paired tactile and scene images selected from VisGel and augmented with sentence-level descriptions through human localization and GPT-4V annotation.

Metadata: Partial Metadata needs review

Quick facts

Vehicle type
Other
Environment
Not reported
Data origin
Real-world
Sensor count
1
Ground truth
Not reported
Calibration
Not reported
Annotations
Available

Sensor overview

High-level sensor availability before the detailed sensor records below.

Ground truth

Reference scope, method, rate, coverage, and provenance.

Not reported

Calibration and synchronization

Reported calibration level, reproducibility signals, and supporting notes.

Level
Not reported
Processed parameters
Not reported
Raw calibration data
Not reported
Calibration targets
Not reported

Calibration data

Calibration reproducibility details are not reported.

Notes

Not reported

Known or intentional limitations

Reported constraints and characteristics to check before using the dataset.

Descriptions of contact material, texture and hardness are generated from visual images using GPT-4V prompts; the paper does not establish independently measured physical-property ground truth.

All noncontact samples use one uniform sentence, so sentence-level language diversity is concentrated in the contact subset.

Section 3.4 reports 19,834 entries; Table 2 reports 19,843 training examples. Their relationship is unresolved.

Cameras

scene_camera

Model
Not reported
Setup
Not Reported
Count
1
Effective cameras
1
Modality
Not Reported
Resolution
Not reported
Rate
Not reported
Shutter
Not Reported
Lens type
Not Reported
HFOV
Not reported
VFOV
Not reported
Notes
VisGel scene images paired with tactile images; TLV selects contact and noncontact frames rather than documenting a full-video release. Camera model, rate and physical count are not given.

IMUs

Not reported

GNSS

Not reported

LiDAR

Not reported

Radar

Not reported

Pitot tube

Not reported

Additional sensors

Other sensor

Name
GelSight tactile sensor
Count
1
Notes
Tactile images inherited from VisGel; GelSight is the reported sensor label, with no exact model or sampling rate. Represented as a tactile input rather than an extra scene camera.

Annotations

Reported annotation availability and task support.

Availability
Available
Format
Not reported
Class count
Not reported
Semantic segmentation Not reported
Instance segmentation Not reported
Object detection Not reported
Optical flow Not reported
Depth ground truth Not reported

Citation

Citation key and BibTeX kept at the end of the page for reference.

Citation key
cheng2024tlv

BibTeX

@misc{cheng2024tlv,
  title={Towards Comprehensive Multimodal Perception: Introducing the Touch-Language-Vision Dataset},
  author={Cheng, Ning and Li, You and Gao, Jing and Fang, Bin and Xu, Jinan and Han, Wenjuan},
  year={2024},
  eprint={2403.09813},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://arxiv.org/abs/2403.09813v3}
}

Dataset corrections

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