41 Result(s)
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Article
Open AccessCross-modal learning using privileged information for long-tailed image classification
The prevalence of long-tailed distributions in real-world data often results in classification models favoring the dominant classes, neglecting the less frequent ones. Current approaches address the issues in ...
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Article
Open AccessLearning to compose diversified prompts for image emotion classification
Image emotion classification (IEC) aims to extract the abstract emotions evoked in images. Recently, language-supervised methods such as contrastive language-image pretraining (CLIP) have demonstrated superior...
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Article
Open AccessVisual attention network
While originally designed for natural language processing tasks, the self-attention mechanism has recently taken various computer vision areas by storm. However, the 2D nature of images brings three challenges...
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Article
Open AccessAltered functional connectivity of the hippocampus with the sensorimotor cortex induced by long-term experience of virtual hand illusion
Synchronizing the movement of a virtual hand with an unseen real hand in a virtual environment is an effective method to induce a sense of ownership of the virtual hand. Although several neuroimaging studies h...
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Article
Open AccessAn efficient algorithm for approximate Voronoi diagram construction on triangulated surfaces
Voronoi diagrams on triangulated surfaces based on the geodesic metric play a key role in many applications of computer graphics. Previous methods of constructing such Voronoi diagrams generally depended on ha...
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Article
Open AccessRecent advances in glinty appearance rendering
The interaction between light and materials is key to physically-based realistic rendering. However, it is also complex to analyze, especially when the materials contain a large number of details and thus exhi...
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Article
Open AccessAttention mechanisms in computer vision: A survey
Humans can naturally and effectively find salient regions in complex scenes. Motivated by this observation, attention mechanisms were introduced into computer vision with the aim of imitating this aspect of th...
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Article
Open AccessAn evaluation of a virtual atlas of portion sizes (VAPS) mobile augmented reality for portion size estimation
Food portion size estimation is a critical yet challenging task in dietary assessment. Augmented reality technology enables the presentation of food dimensions and volume in a virtual three-dimensional object....
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Article
Open AccessA simplified ICA-based local similarity stereo matching
Since the existing stereo matching methods may fail in the regions of non-textures, boundaries and tiny details, a simplified independent component correlation algorithm (ICA)-based local similarity stereo mat...
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Chapter and Conference Paper
PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report
This paper reviews the first challenge on efficient perceptual image enhancement with the focus on deploying deep learning models on smartphones. The challenge consisted of two tracks. In the first one, partic...
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Chapter and Conference Paper
VisDrone-SOT2018: The Vision Meets Drone Single-Object Tracking Challenge Results
Single-object tracking, also known as visual tracking, on the drone platform attracts much attention recently with various applications in computer vision, such as filming and surveillance. However, the lack o...
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Chapter and Conference Paper
Removal of Visual Disruption Caused by Rain Using Cycle-Consistent Generative Adversarial Networks
This paper addresses the problem of removing rain disruption from images for outdoor vision systems. The Cycle-Consistent Generative Adversarial Network (CycleGAN) is proposed as a more promising rain removal ...
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Chapter and Conference Paper
Exploiting Vector Fields for Geometric Rectification of Distorted Document Images
This paper proposes a segment-free method for geometric rectification of a distorted document image captured by a hand-held camera. The method can recover the 3D page shape by exploiting the intrinsic vector f...
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Chapter and Conference Paper
On Regularized Losses for Weakly-supervised CNN Segmentation
Minimization of regularized losses is a principled approach to weak supervision well-established in deep learning, in general. However, it is largely overlooked in semantic segmentation currently dominated by ...
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Chapter and Conference Paper
Efficient Relative Attribute Learning Using Graph Neural Networks
A sizable body of work on relative attributes provides evidence that relating pairs of images along a continuum of strength pertaining to a visual attribute yields improvements in a variety of vision tasks. In...
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Article
Open AccessSemi-supervised dictionary learning with label propagation for image classification
Sparse coding and supervised dictionary learning have rapidly developed in recent years, and achieved impressive performance in image classification. However, there is usually a limited number of labeled train...
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Chapter and Conference Paper
Robust 3D Indoor Map Building via RGB-D SLAM with Adaptive IMU Fusion on Robot
Building a 3D map of indoor environment is a prerequisite for various applications, ranging from service robot to augmented reality, where RGB-D SLAM is a commonly used technique. To efficiently and robustly b...
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Chapter and Conference Paper
A Quality Evaluation Scheme to 3D Printing Objects Using Stereovision Measurement
The paper presents a comprehensive evaluation method on shape consistency by using three-dimensional scanning, reverse engineering and post-processing. The complete evaluation scheme includes data collection,...
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Chapter and Conference Paper
Real-Time Multi-camera Video Stitching Based on Improved Optimal Stitch Line and Multi-resolution Fusion
In this paper, we propose a multi-camera video stitching method based on an improved optimal stitch line and multi-resolution for real-time application. First, phase correlation is used to estimate overlap**...
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Chapter and Conference Paper
NexP: A Beginner Friendly Toolkit for Designing and Conducting Controlled Experiments
In this paper, we introduce NexP (Next Experiment Toolkit), an open-source toolkit for designing and running controlled experiments. Unlike previous toolkits, it is targeted for the unmet needs of the beginners i...
