ThinObject-5K

ThinObject-5K is a high-resolution dataset for thin object segmentation, containing 5,748 images with pixel-accurate binary ground-truth masks that emphasize thin structures (e.g. wires, legs, handles, wineglass stems, antennae).

Splits

Split	Rows	Source list
train	5248	official trainval.txt
test	500	official test.txt

The two splits are disjoint and together cover all 5,748 image/mask pairs. The original repository additionally provides a train.txt (4,748) / validation (500) partition; the validation subset is folded into the train split here and is recoverable from the original lists if needed.

Schema

Column	Type	Description
image	Image	RGB photograph (JPEG)
mask	Image	Single-channel (mode L) binary ground-truth segmentation mask, same resolution as the image

Source & Credit

This dataset was introduced in:

Deep Interactive Thin Object Selection Jun Hao Liew, Scott Cohen, Brian Price, Long Mai, Jiashi Feng. WACV 2021.

Original repository: https://github.com/liewjunhao/thin-object-selection

Original data (Google Drive) is redistributed here for convenience. All credit belongs to the original authors. Please cite the paper above when using this dataset.

License

Released under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license, matching the license of the original thin-object-selection repository. Non-commercial use only.