Panoramic depth estimation via supervised and unsupervised learning in indoor scenes-Reference-Cited by-同舟云学术

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Panoramic depth estimation via supervised and unsupervised learning in indoor scenes

Published:2021-09-10 Issue:26 Volume:60 Page:8188
ISSN:1559-128X
Container-title:Applied Optics
language:en
Short-container-title:Appl. Opt.

Author:

Zhou Keyang,Yang Kailun,Wang Kaiwei

Funder

ZJU-Sunny Photonics Innovation Center

Bundesministerium für Arbeit und Soziales

Publisher

The Optical Society

Subject

Atomic and Molecular Physics, and Optics,Engineering (miscellaneous),Electrical and Electronic Engineering

Reference43 articles.

1. ACNet: Attention based network to exploit complementary features for RGBD semantic segmentation;Hu,2019

2. Robustifying semantic cognition of traversability across wearable RGB-depth cameras

3. Real-Time Fusion Network for RGB-D Semantic Segmentation Incorporating Unexpected Obstacle Detection for Road-Driving Images

4. Polarization-driven semantic segmentation via efficient attention-bridged fusion

5. Stereo Processing by Semiglobal Matching and Mutual Information

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3. Spatio-Temporal Fusion of LiDAR and Camera Data for Omnidirectional Depth Perception;Transportation Research Record: Journal of the Transportation Research Board;2023-07-24

4. Dense Depth Completion Based on Multi-Scale Confidence and Self-Attention Mechanism for Intestinal Endoscopy;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

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