ADU-Depth: Attention-based Distillation with Uncertainty Modeling for Depth Estimation

no code implementations • 26 Sep 2023 • Zizhang Wu, Zhuozheng Li, Zhi-Gang Fan, Yunzhe Wu, Xiaoquan Wang, Rui Tang, Jian Pu

Monocular depth estimation is challenging due to its inherent ambiguity and ill-posed nature, yet it is quite important to many applications.

Domain Adaptation Knowledge Distillation +2

Learning Monocular Depth in Dynamic Environment via Context-aware Temporal Attention

no code implementations • 12 May 2023 • Zizhang Wu, Zhuozheng Li, Zhi-Gang Fan, Yunzhe Wu, Yuanzhu Gan, Jian Pu, Xianzhi Li

During the refinement process, context-aware temporal attention (CTA) is developed to capture the global temporal-context correlations to maintain the feature consistency and estimation integrity of moving objects.

Autonomous Driving Monocular Depth Estimation +1