most citedGasMono: Geometry-Aided Self-Supervised Monocular Depth Estimation for Indoor Scenes

2 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Self-Supervised Monocular Depth Estimation in the Dark: Towards Data Distribution Compensation

Haolin Yang, Chaoqiang Zhao, Lu Sheng +1

Nighttime self-supervised monocular depth estimation has received increasing attention in recent years. However, using night images for self-supervision is unreliable because the p…

cs.CV20232 cited

GasMono: Geometry-Aided Self-Supervised Monocular Depth Estimation for Indoor Scenes

Chaoqiang Zhao, Matteo Poggi, Fabio Tosi +4

This paper tackles the challenges of self-supervised monocular depth estimation in indoor scenes caused by large rotation between frames and low texture. We ease the learning proce…

cs.CV20231 cited

Causal reasoning in typical computer vision tasks

Kexuan Zhang, Qiyu Sun, Chaoqiang Zhao +1

Deep learning has revolutionized the field of artificial intelligence. Based on the statistical correlations uncovered by deep learning-based methods, computer vision has contribut…

cs.CV20232 cited

CMDA: Cross-Modality Domain Adaptation for Nighttime Semantic Segmentation

Ruihao Xia, Chaoqiang Zhao, Meng Zheng +3

Most nighttime semantic segmentation studies are based on domain adaptation approaches and image input. However, limited by the low dynamic range of conventional cameras, images fa…

cs.CV2023

The Second Monocular Depth Estimation Challenge

Jaime Spencer, C. Stella Qian, Michaela Trescakova +40

This paper discusses the results for the second edition of the Monocular Depth Estimation Challenge (MDEC). This edition was open to methods using any form of supervision, includin…