News
[08/2022] Our work on TransNet was accepted by ECCV2022 Workshop!
[07/2022] Our work on Clearpose was accepted by ECCV2022!
[06/2022] Our work on Progresslabeller was accepted by IROS2022!
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TransNet: Category-Level Transparent Object Pose Estimation
Huijie Zhang,
Anthony Opipari,
Xiaotong Chen,
Jiyue Zhu,
Zeren Yu,
Odest Chadwicke Jenkins,
ECCV Workshop, 2022
arXiv
/website
We proposed TransNet, a two-stage pipeline that learns to estimate category-level transparent object pose using localized depth completion and surface normal estimation.
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ClearPose: Large-scale Transparent Object Dataset and Benchmark
Xiaotong Chen,
Huijie Zhang,
Zeren Yu,
Anthony Opipari,
Odest Chadwicke Jenkins,
ECCV, 2022
arXiv
/github
/website
We collected a large-scale transparent object dataset with RGB-D and annotated poses.
And we benchmarked transparent object depth completion and poes estimation on this dataset.
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ProgressLabeller: Visual Data Stream Annotation for Training Object-Centric 3D Perception
Xiaotong Chen,
Huijie Zhang,
Zeren Yu,
Stanley Lewis,
Odest Chadwicke Jenkins,
IROS, 2022
arXiv
/github
/website
ProgressLabeller is an efficient 6D pose annotation method. It is also the first open source tools compatible with transparent object.
It was implemented as a blender Add-on, more user-friendly for using.
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