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.
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.
no code implementations • 8 Dec 2022 • Zizhang Wu, Yuanzhu Gan, Xianzhi Li, Yunzhe Wu, Xiaoquan Wang, Tianhao Xu, Fan Wang
Most existing networks based on public datasets may generalize suboptimal results on these valet parking scenes, also affected by the fisheye distortion.
no code implementations • 30 Nov 2022 • Zizhang Wu, Yunzhe Wu, Jian Pu, Xianzhi Li, Xiaoquan Wang
Specifically, we leverage intermediate features and responses for knowledge distillation.