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Yundong Li, Xiaokun Wei and Hanlu Fan
Monocular depth estimation (MDE), as one of the fundamental tasks of computer vision, plays important roles in downstream applications such as virtual reality, 3D reconstruction, and robotic navigation. Convolutional neural networks (CNN)-based methods g...
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Abdullah Jan and Suyoung Seo
Depth maps are single image metrics that carry the information of a scene in three-dimensional axes. Accurate depth maps can recreate the 3D structure of a scene, which helps in understanding the full geometry of the objects within the scene. Depth maps ...
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Dexiao Kong, Jiayi Wang, Qinghui Zhang, Junqiu Li and Jian Rong
Automated fruit-picking equipment has the potential to significantly enhance the efficiency of picking. Accurate detection and localization of fruits are particularly crucial in this regard. However, current methods rely on expensive tools such as depth ...
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Ting-Hui Chiang, Meng-Hsiu Chiang, Ming-Han Tsai and Che-Cheng Chang
While many monocular depth estimation methods have been proposed, determining depth variations in outdoor scenes remains challenging. Accordingly, this paper proposes an image segmentation-based monocular depth estimation model with attention mechanisms ...
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Hyeseung Park and Seungchul Park
In this paper, we propose a novel unsupervised learning-based model for estimating the depth of monocular images by integrating a simple ResNet-based auto-encoder and some special loss functions. We use only stereo images obtained from binocular cameras ...
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Ricardo Oliva-García, Sabato Ceruso, José G. Marichal-Hernández and José M. Rodriguez-Ramos
This work introduces a real-time full-resolution depth estimation device, which allows integral displays to be fed with a real-time light-field. The core principle of the technique is a high-speed focal stack acquisition method combined with an efficient...
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Junhao Cheng, Zhi Wang, Hongyan Zhou, Li Li and Jian Yao
Most Simultaneous Localization and Mapping (SLAM) methods assume that environments are static. Such a strong assumption limits the application of most visual SLAM systems. The dynamic objects will cause many wrong data associations during the SLAM proces...
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Guolai Jiang, Shaokun Jin, Yongsheng Ou and Shoujun Zhou
The depth estimation of the 3D deformable object has become increasingly crucial to various intelligent applications. In this paper, we propose a feature-based approach for accurate depth estimation of a deformable 3D object with a single camera, which r...
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Qianru Teng, Yimin Chen and Chen Huang
We present an occlusion-aware unsupervised neural network for jointly learning three low-level vision tasks from monocular videos: depth, optical flow, and camera motion. The system consists of three different predicting sub-networks simultaneously coupl...
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