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The study of stereo matching optimization based on multi-baseline trinocular model
The huge computational complexity, occlusion and low texture region problems make stereo matching a big challenge. In this work, we use …
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A Study of General Data Improvement for Large-Angle Head Pose Estimation
Predicting Euler angles of head pose using end-to-end CNN from a single RGB image is a popular application in recent years. However, …
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Omnidirectional stereo depth estimation based on spherical deep network
Omnidirectional depth estimation is an emerging research topic and has received significant attention in recent years. However, the …
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A Review on Quantitative Analyzing Axonal Transport of Mitochondria
The movements of mitochondrial are especially critical for neuronal growth and function. However, to analyze and quantify this process …
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Pixel-level Diabetic Retinopathy Lesion Detection Using Multi-scale Convolutional Neural Network
Diabetic retinopathy (DR) is one of the leading causes of preventable blindness. It’s urgent to develop reliable methods for auto …
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Image Processing: Facilitating Retinanet for Detecting Small Objects
Detecting small objects is a challenging task in object detection due to low spatial resolution and interference by background. …
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GazeFollowTR: A Method of Gaze Following with Reborn Mechanism
Most existing 3D pose representations cannot completely decouple the overlapping two or more human joints of the same type. In this …
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MMDA: Multi-person Marginal Distribution Awareness for Monocular 3D Pose Estimation
Most existing 3D pose representations cannot completely decouple the overlapping two or more human joints of the same type. In this …
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Pyramid Feature Attention Network for Monocular Depth Prediction
Deep convolutional neural networks (DCNNs) have achieved great success in monocular depth estimation (MDE). However, few existing works …
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The multi-learning for food analyses in computer vision: a survey
With the rapid development of food production and health management, analyses of food samples have been essential for preventing …
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