315 citations · 861 across the 17 of their papers we have counts for
17 papers
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…
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…
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…
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…
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…
The Monocular Depth Estimation Challenge
Jaime Spencer, C. Stella Qian, Chris Russell +16
This paper summarizes the results of the first Monocular Depth Estimation Challenge (MDEC) organized at WACV2023. This challenge evaluated the progress of self-supervised monocular…
Towards Generalization on Real Domain for Single Image Dehazing via Meta-Learning
Wenqi Ren, Qiyu Sun, Chaoqiang Zhao +1
Learning-based image dehazing methods are essential to assist autonomous systems in enhancing reliability. Due to the domain gap between synthetic and real domains, the internal in…
Visual Semantic Segmentation Based on Few/Zero-Shot Learning: An Overview
Wenqi Ren, Yang Tang, Qiyu Sun +2
Visual semantic segmentation aims at separating a visual sample into diverse blocks with specific semantic attributes and identifying the category for each block, and it plays a cr…
MonoViT: Self-Supervised Monocular Depth Estimation with a Vision Transformer
Chaoqiang Zhao, Youmin Zhang, Matteo Poggi +6
Self-supervised monocular depth estimation is an attractive solution that does not require hard-to-source depth labels for training. Convolutional neural networks (CNNs) have recen…
Learn to Adapt for Monocular Depth Estimation
Qiyu Sun, Gary G. Yen, Yang Tang +1
Monocular depth estimation is one of the fundamental tasks in environmental perception and has achieved tremendous progress in virtue of deep learning. However, the performance of…
Unsupervised Monocular Depth Estimation in Highly Complex Environments
Chaoqiang Zhao, Yang Tang, Qiyu Sun
With the development of computational intelligence algorithms, unsupervised monocular depth and pose estimation framework, which is driven by warped photometric consistency, has sh…
Multi-task GANs for Semantic Segmentation and Depth Completion with Cycle Consistency
Chongzhen Zhang, Yang Tang, Chaoqiang Zhao +3
Semantic segmentation and depth completion are two challenging tasks in scene understanding, and they are widely used in robotics and autonomous driving. Although several works are…
Masked GANs for Unsupervised Depth and Pose Prediction with Scale Consistency
Chaoqiang Zhao, Gary G. Yen, Qiyu Sun +2
Previous work has shown that adversarial learning can be used for unsupervised monocular depth and visual odometry (VO) estimation, in which the adversarial loss and the geometric…
When Autonomous Systems Meet Accuracy and Transferability through AI: A Survey
Chongzhen Zhang, Jianrui Wang, Gary G. Yen +5
With widespread applications of artificial intelligence (AI), the capabilities of the perception, understanding, decision-making and control for autonomous systems have improved si…
Monocular Depth Estimation Based On Deep Learning: An Overview
Chaoqiang Zhao, Qiyu Sun, Chongzhen Zhang +2
Depth information is important for autonomous systems to perceive environments and estimate their own state. Traditional depth estimation methods, like structure from motion and st…
Perception and Navigation in Autonomous Systems in the Era of Learning: A Survey
Yang Tang, Chaoqiang Zhao, Jianrui Wang +6
Autonomous systems possess the features of inferring their own state, understanding their surroundings, and performing autonomous navigation. With the applications of learning syst…
Deep Direct Visual Odometry
Chaoqiang Zhao, Yang Tang, Qiyu Sun +1
Traditional monocular direct visual odometry (DVO) is one of the most famous methods to estimate the ego-motion of robots and map environments from images simultaneously. However,…