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Zhuozheng Li

2 accepted papers

2023

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

CoRL 2023poster

Monocular depth estimation is challenging due to its inherent ambiguity and ill-posed nature, yet it is quite important to many applications. While recent works achieve limited accuracy by designing increasingly complicated networks to extract features with limited spatial geometric cues from a sing…

Cited by 2SourceScholar
2023

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

IJCAI 2023poster

The monocular depth estimation task has recently revealed encouraging prospects, especially for the autonomous driving task. To tackle the ill-posed problem of 3D geometric reasoning from 2D monocular images, multi-frame monocular methods are developed to leverage the perspective correlation informa…

Cited by 0SourcePDFScholar