Search Results for author: Junyu Zhu

Found 4 papers, 2 papers with code

Self-supervised Event-based Monocular Depth Estimation using Cross-modal Consistency

no code implementations14 Jan 2024 Junyu Zhu, Lina Liu, Bofeng Jiang, Feng Wen, Hongbo Zhang, Wanlong Li, Yong liu

In this paper, to lower the annotation cost, we propose a self-supervised event-based monocular depth estimation framework named EMoDepth.

Depth Prediction Monocular Depth Estimation

Camera-based 3D Semantic Scene Completion with Sparse Guidance Network

1 code implementation10 Dec 2023 Jianbiao Mei, Yu Yang, Mengmeng Wang, Junyu Zhu, Xiangrui Zhao, Jongwon Ra, Laijian Li, Yong liu

Semantic scene completion (SSC) aims to predict the semantic occupancy of each voxel in the entire 3D scene from limited observations, which is an emerging and critical task for autonomous driving.

3D Semantic Scene Completion Autonomous Driving

Semi-Supervised Learning for Visual Bird's Eye View Semantic Segmentation

1 code implementation28 Aug 2023 Junyu Zhu, Lina Liu, Yu Tang, Feng Wen, Wanlong Li, Yong liu

In this paper, we present a novel semi-supervised framework for visual BEV semantic segmentation to boost performance by exploiting unlabeled images during the training.

Autonomous Vehicles Bird's-Eye View Semantic Segmentation +2

FG-Depth: Flow-Guided Unsupervised Monocular Depth Estimation

no code implementations20 Jan 2023 Junyu Zhu, Lina Liu, Yong liu, Wanlong Li, Feng Wen, Hongbo Zhang

The great potential of unsupervised monocular depth estimation has been demonstrated by many works due to low annotation cost and impressive accuracy comparable to supervised methods.

Image Reconstruction Monocular Depth Estimation +2

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