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pro vyhledávání: '"Qiao, Rukun"'
We introduce a novel depth estimation technique for multi-frame structured light setups using neural implicit representations of 3D space. Our approach employs a neural signed distance field (SDF), trained through self-supervised differentiable rende
Externí odkaz:
http://arxiv.org/abs/2405.12006
In recent years, deep neural networks have shown remarkable progress in dense disparity estimation from dynamic scenes in monocular structured light systems. However, their performance significantly drops when applied in unseen environments. To addre
Externí odkaz:
http://arxiv.org/abs/2310.08934
Publikováno v:
IEEE Robotics and Automation Letters ( Volume: 7, Issue: 2, April 2022). pp 5111 - 5118
We introduced Temporally Incremental Disparity Estimation Network (TIDE-Net), a learning-based technique for disparity computation in mono-camera structured light systems. In our hardware setting, a static pattern is projected onto a dynamic scene an
Externí odkaz:
http://arxiv.org/abs/2310.08932
Akademický článek
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