AIMC Topic: Vision Disparity

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Depth Perception Based on the Interaction of Binocular Disparity and Motion Parallax Cues in Three-Dimensional Space.

Sensors (Basel, Switzerland)
BACKGROUND AND OBJECTIVES: Depth perception of the human visual system in three-dimensional (3D) space plays an important role in human-computer interaction and artificial intelligence (AI) areas. It mainly employs binocular disparity and motion para...

Transformer Based Binocular Disparity Prediction with Occlusion Predict and Novel Full Connection Layers.

Sensors (Basel, Switzerland)
The depth estimation algorithm based on the convolutional neural network has many limitations and defects by constructing matching cost volume to calculate the disparity: using a limited disparity range, the authentic disparity beyond the predetermin...

Parallax attention stereo matching network based on the improved group-wise correlation stereo network.

PloS one
Recent stereo matching methods, especially end-to-end deep stereo matching networks, have achieved remarkable performance in the fields of autonomous driving and depth sensing. However, state-of-the-art stereo algorithms, even with the deep neural ne...

Emergence of Binocular Disparity Selectivity through Hebbian Learning.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Neural selectivity in the early visual cortex strongly reflects the statistics of our environment (Barlow, 2001; Geisler, 2008). Although this has been described extensively in literature through various encoding hypotheses (Barlow and Földiák, 1989;...

Binocular vision supports the development of scene segmentation capabilities: Evidence from a deep learning model.

Journal of vision
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...