English(EN) Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision

新框架将RGB基础模型重新用于热深度估计

作者 PulseAugur 编辑部 · [1 个来源] · 2026-08-13 04:00

研究人员开发了RGB-HS，一个旨在通过利用基于RGB的基础模型来改进热图像深度估计的新框架。该方法利用分层监督，在RGB教师分支和热学生分支之间对多层表示进行对齐。该框架还包含一个验证步骤，通过根据图像质量对RGB token进行加权来优化对齐，从而在基准测试中取得有竞争力的性能。 AI

影响增强了基础模型在热深度估计等专业视觉任务中的效用。

排序理由该集群包含一篇详细介绍计算机视觉任务新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Jie Hong, Tingtian Li, Xuesong Li, Xiao Li · 2026-08-13 04:00

利用基于RGB的视觉基础模型通过分层监督进行热成像深度估计的再利用

arXiv:2608.11564v1 Announce Type: new Abstract: Depth estimation from thermal images is highly valuable for robotic applications in adverse conditions, such as nighttime and rainy weather. Recent studies have sought to transfer knowledge from RGB-based foundation models to therma…