Online Continual Learning (OCL) addresses the problem of training neural...
Deep neural networks have shown remarkable performance when trained on
i...
Explainable artificial intelligence (XAI) has witnessed significant adva...
We address personalized image enhancement in this study, where we enhanc...
In this study, we address local photo enhancement to improve the aesthet...
Open-set semi-supervised object detection (OSSOD) methods aim to utilize...
Online knowledge distillation (KD) has received increasing attention in
...
The number of traffic accidents has been continuously increasing in rece...
Supervised learning methods have been suffering from the fact that a
lar...
This paper proposes an attribute-guided multi-level attention network
(A...
Although Convolutional Neural Networks (CNNs) have high accuracy in imag...
The ground motion prediction equation is commonly used to predict the se...
This paper presents a self-adaptive training (SAT) model for fashion
com...
Adversarial attacks have only focused on changing the predictions of the...
We present an efficient approach for Masked Image Modeling (MIM) with
hi...
In this paper, we present novel synthetic training data called self-blen...
Self-supervised learning (SSL) has made enormous progress and largely
na...
This study presents a new user experience in apartment searches using
fu...
Graph Neural Networks (GNNs) are deep learning models that take graph da...
Unsupervised video-based person re-identification (re-ID) methods extrac...
Shadow removal is an essential task in computer vision and computer grap...
With expansion of the video advertising market, research to predict the
...
In recent years, deep neural networks (DNNs) have achieved equivalent or...
In this paper, we present a novel image inpainting technique using frequ...
Re-identification (re-ID) is currently investigated as a closed-world im...
Pretext tasks and contrastive learning have been successful in
self-supe...
In this study, we address image retargeting, which is a task that adjust...
We propose a self-supervised method to learn feature representations fro...
The spread of social networking services has created an increasing deman...
Recently, 3D convolutional networks (3D ConvNets) yield good performance...
In this paper, we study the generalization properties of neural networks...
Background and Objective: Object detection is a primary research interes...
Recently, 3D convolutional networks yield good performance in action
rec...
This paper aims to evaluate the suitability of current deep learning met...
Conventional video summarization approaches based on reinforcement learn...
In this paper, we propose a new measure to estimate the similarity betwe...
This paper tackles unpaired image enhancement, a task of learning a mapp...
This paper tackles a new problem setting: reinforcement learning with
pi...
In this paper we propose a method that can enhance the social popularity...
Weakly supervised object detection (WSOD), where a detector is trained w...
Image restoration is a technique that reconstructs a feasible estimate o...
Our paper introduces an efficient combination of established techniques ...
This paper tackles a new problem setting: reinforcement learning with
pi...
Can we detect common objects in a variety of image domains without
insta...
Deep neural networks (DNNs) trained on large-scale datasets have exhibit...
With the growth of digitized comics, image understanding techniques are
...
This paper introduces a deep learning based classifier for common skin
a...
Data clustering is a fundamental operation in data analysis. For handlin...
We propose the residual expansion (RE) algorithm: a global (or near-glob...
Manga (Japanese comics) are popular worldwide. However, current e-manga
...