AIMC Topic: Depth Perception

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Learning Receptive Fields and Quality Lookups for Blind Quality Assessment of Stereoscopic Images.

IEEE transactions on cybernetics Apr 9, 2015
Blind quality assessment of 3D images encounters more new challenges than its 2D counterparts. In this paper, we propose a blind quality assessment for stereoscopic images by learning the characteristics of receptive fields (RFs) from perspective of ...
Imaging, Three-Dimensional Models, Neurological Algorithms Depth Perception Computer Simulation Humans Machine Learning
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Semantic discrete decoder based on adaptive pixel clustering for monocular depth estimation.

Neural networks : the official journal of the International Neural Network Society Sep 1, 2025
Monocular depth estimation (MDE) has long been a popular and challenging task. Currently, mainstream methods mainly include regression methods based on geometric constraints and ordinal regression methods based on discretized depth intervals. However...
Depth Perception Vision, Monocular Humans Neural Networks, Computer Algorithms Cluster Analysis Semantics
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Real-time and accurate stereo matching via tri-fusion volume for stereo vision.

Neural networks : the official journal of the International Neural Network Society Sep 1, 2025
In the field of real-time stereo matching, a concise and informative cost volume is crucial for achieving high efficiency and accuracy. To this end, in this paper, we propose the Tri-Fusion Volume (TFV) to effectively fuse both texture details and si...
Image Processing, Computer-Assisted Humans Pattern Recognition, Automated Neural Networks, Computer Depth Perception Algorithms Deep Learning Imaging, Three-Dimensional
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DASNeRF: depth consistency optimization, adaptive sampling, and hierarchical structural fusion for sparse view neural radiance fields.

PloS one Jan 1, 2025
To address the challenges of significant detail loss in Neural Radiance Fields (NeRF) under sparse-view input conditions, this paper proposes the DASNeRF framework. DASNeRF aims to generate high-detail novel views from a limited number of input viewp...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Depth Perception Algorithms Imaging, Three-Dimensional
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Binocular vision supports the development of scene segmentation capabilities: Evidence from a deep learning model.

Journal of vision Jul 6, 2021
The application of deep learning techniques has led to substantial progress in solving a number of critical problems in machine vision, including fundamental problems of scene segmentation and depth estimation. Here, we report a novel deep neural net...
Humans Deep Learning Vision Disparity Depth Perception Vision, Binocular
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Towards a Machine-Learning Approach for Sickness Prediction in 360° Stereoscopic Videos.

IEEE transactions on visualization and computer graphics Apr 1, 2018
Virtual reality systems are widely believed to be the next major computing platform. There are, however, some barriers to adoption that must be addressed, such as that of motion sickness - which can lead to undesirable symptoms including postural ins...
Depth Perception Motion Sickness Middle Aged User-Computer Interface Video Recording Computer Graphics Virtual Reality Adult Humans Male Female Algorithms Young Adult Databases, Factual Machine Learning
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Technology: The Future of Agriculture.

Nature Apr 26, 2017
Vegetables Pesticides Technology Transfer Agrochemicals Animal Husbandry Automation Animal Diseases Fruit Plant Weeds Lasers Depth Perception Abattoirs Quality Control Animals Remote Sensing Technology Plant Diseases Crop Production Clinical Alarms Livestock Agriculture Time Factors Machine Learning Monitoring, Physiologic Mobile Applications Soil Robotics
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