TOSN-Trans：Transparent Object Segmentation Network with Transformer
RGB-D;glass segmentation;feature fusion;dual-network;efficient transformer;boundary optimization
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Submission Desk Rejected by Program Chairs
@misc{
tao2024tosntranstransparent,
title={{TOSN}-Trans：Transparent Object Segmentation Network with Transformer},
author={Tao Tao},
year={2024},
url={https://openreview.net/forum?id=Rhclu9eWxU}
}
Due to the optical properties of glass materials, most glass appears transparent in RGB images. However, in depth images, different acquisition methods make glass visible. Therefore, Therefore, using RGB-D dual-channel feature input makes it easier to recognize and segment glass objects. Building on this concept, we propose a multi-layer symmetrical dual-channel network architecture, which can effectively realize trans-modal feature fusion of RGB-D images based on attention mechanism, and integrate Convolutional and Transformer architectures to extract local features and non-local dependencies, respectively. To further enhance segmentation accuracy and efficiency, this paper also designs a boundary optimization module. This module constructs a distance map based on edge prediction guidance, enabling high-precision glass edge recognition. To support this work, we collect a new dataset comprising 5551 sets of calibrated RGB-D images. The effectiveness and accuracy of the proposed glass segmentation method are rigorously evaluated quantitatively and qualitatively. The code for this paper has been published at:https://github.com/Jaccury/RGB-D-Transparent-object-segmentation.
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Tao Tao
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RGB-D glass segmentation feature fusion dual-network efficient transformer boundary optimization
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tao|tosntranstransparent_object_segmentation_network_with_transformer
/pdf/1489e79ca08ea09dc7e6af72a1db7ae1a218bfe4.pdf
applications to computer vision, audio, language, and other modalities
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TOSN-Trans：Transparent Object Segmentation Network with Transformer
ICLR 2025 Conference Desk Rejected Submission
ICLR.cc/2025/Conference/Desk_Rejected_Submission