30 citations · 110 across the 14 of their papers we have counts for
14 papers
Age Prediction From Face Images Via Contrastive Learning
Yeongnam Chae, Poulami Raha, Mijung Kim +1
This paper presents a novel approach for accurately estimating age from face images, which overcomes the challenge of collecting a large dataset of individuals with the same identi…
LLDiffusion: Learning Degradation Representations in Diffusion Models for Low-Light Image Enhancement
Tao Wang, Kaihao Zhang, Ziqian Shao +5
Current deep learning methods for low-light image enhancement (LLIE) typically rely on pixel-wise mapping learned from paired data. However, these methods often overlook the import…
GridFormer: Residual Dense Transformer with Grid Structure for Image Restoration in Adverse Weather Conditions
Tao Wang, Kaihao Zhang, Ziqian Shao +6
Image restoration in adverse weather conditions is a difficult task in computer vision. In this paper, we propose a novel transformer-based framework called GridFormer which serves…
Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based Method
Tao Wang, Kaihao Zhang, Tianrun Shen +3
As the quality of optical sensors improves, there is a need for processing large-scale images. In particular, the ability of devices to capture ultra-high definition (UHD) images a…
UserBERT: Modeling Long- and Short-Term User Preferences via Self-Supervision
Tianyu Li, Ali Cevahir, Derek Cho +3
E-commerce platforms generate vast amounts of customer behavior data, such as clicks and purchases, from millions of unique users every day. However, effectively using this data fo…
Deep Image Deblurring: A Survey
Kaihao Zhang, Wenqi Ren, Wenhan Luo +4
Image deblurring is a classic problem in low-level computer vision with the aim to recover a sharp image from a blurred input image. Advances in deep learning have led to significa…
MC-Blur: A Comprehensive Benchmark for Image Deblurring
Kaihao Zhang, Tao Wang, Wenhan Luo +6
Blur artifacts can seriously degrade the visual quality of images, and numerous deblurring methods have been proposed for specific scenarios. However, in most real-world images, bl…
Deblurring by Realistic Blurring
Kaihao Zhang, Wenhan Luo, Yiran Zhong +4
Existing deep learning methods for image deblurring typically train models using pairs of sharp images and their blurred counterparts. However, synthetically blurring images do not…
Learning Classifiers on Positive and Unlabeled Data with Policy Gradient
Tianyu Li, Chien-Chih Wang, Yukun Ma +4
Existing algorithms aiming to learn a binary classifier from positive (P) and unlabeled (U) data generally require estimating the class prior or label noises ahead of building a cl…
Deep Heterogeneous Autoencoders for Collaborative Filtering
Tianyu Li, Yukun Ma, Jiu Xu +3
This paper leverages heterogeneous auxiliary information to address the data sparsity problem of recommender systems. We propose a model that learns a shared feature space from het…
RGB-based 3D Hand Pose Estimation via Privileged Learning with Depth Images
Shanxin Yuan, Bjorn Stenger, Tae-Kyun Kim
This paper proposes a method for hand pose estimation from RGB images that uses both external large-scale depth image datasets and paired depth and RGB images as privileged informa…
Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals
Shanxin Yuan, Guillermo Garcia-Hernando, Bjorn Stenger +21
In this paper, we strive to answer two questions: What is the current state of 3D hand pose estimation from depth images? And, what are the next challenges that need to be tackled?…
BigHand2.2M Benchmark: Hand Pose Dataset and State of the Art Analysis
Shanxin Yuan, Qi Ye, Bjorn Stenger +2
In this paper we introduce a large-scale hand pose dataset, collected using a novel capture method. Existing datasets are either generated synthetically or captured using depth sen…
Pano2CAD: Room Layout From A Single Panorama Image
Jiu Xu, Bjorn Stenger, Tommi Kerola +1
This paper presents a method of estimating the geometry of a room and the 3D pose of objects from a single 360-degree panorama image. Assuming Manhattan World geometry, we formulat…