Search Results for author: Bjorn Stenger

Found 21 papers, 7 papers with code

Age Prediction From Face Images Via Contrastive Learning

no code implementations23 Aug 2023 Yeongnam Chae, Poulami Raha, Mijung Kim, Bjorn Stenger

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 identity at different ages.

Contrastive Learning MORPH +1

LLDiffusion: Learning Degradation Representations in Diffusion Models for Low-Light Image Enhancement

1 code implementation27 Jul 2023 Tao Wang, Kaihao Zhang, Ziqian Shao, Wenhan Luo, Bjorn Stenger, Tae-Kyun Kim, Wei Liu, Hongdong Li

In this paper, we address this limitation by proposing a degradation-aware learning scheme for LLIE using diffusion models, which effectively integrates degradation and image priors into the diffusion process, resulting in improved image enhancement.

Image Generation Low-Light Image Enhancement

Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based Method

1 code implementation22 Dec 2022 Tao Wang, Kaihao Zhang, Tianrun Shen, Wenhan Luo, Bjorn Stenger, Tong Lu

In this paper, we consider the task of low-light image enhancement (LLIE) and introduce a large-scale database consisting of images at 4K and 8K resolution.

4k 8k +3

UserBERT: Modeling Long- and Short-Term User Preferences via Self-Supervision

no code implementations14 Feb 2022 Tianyu Li, Ali Cevahir, Derek Cho, Hao Gong, DuyKhuong Nguyen, Bjorn Stenger

This paper extends the BERT model to e-commerce user data for pre-training representations in a self-supervised manner.

Representation Learning

Deep Image Deblurring: A Survey

no code implementations26 Jan 2022 Kaihao Zhang, Wenqi Ren, Wenhan Luo, Wei-Sheng Lai, Bjorn Stenger, Ming-Hsuan Yang, Hongdong Li

Image deblurring is a classic problem in low-level computer vision with the aim to recover a sharp image from a blurred input image.

Deblurring Deep Learning +2

MC-Blur: A Comprehensive Benchmark for Image Deblurring

2 code implementations1 Dec 2021 Kaihao Zhang, Tao Wang, Wenhan Luo, Boheng Chen, Wenqi Ren, Bjorn Stenger, Wei Liu, Hongdong Li, Ming-Hsuan Yang

Blur artifacts can seriously degrade the visual quality of images, and numerous deblurring methods have been proposed for specific scenarios.

Benchmarking Deblurring +1

Benchmarking Ultra-High-Definition Image Super-Resolution

no code implementations ICCV 2021 Kaihao Zhang, Dongxu Li, Wenhan Luo, Wenqi Ren, Bjorn Stenger, Wei Liu, Hongdong Li, Ming-Hsuan Yang

Increasingly, modern mobile devices allow capturing images at Ultra-High-Definition (UHD) resolution, which includes 4K and 8K images.

4k 8k +3

UserBERT: Self-supervised User Representation Learning

no code implementations1 Jan 2021 Tianyu Li, Ali Cevahir, Derek Cho, Hao Gong, DuyKhuong Nguyen, Bjorn Stenger

This paper extends the BERT model to user data for pretraining user representations in a self-supervised way.

Multi-Task Learning Representation Learning

Deblurring by Realistic Blurring

1 code implementation CVPR 2020 Kaihao Zhang, Wenhan Luo, Yiran Zhong, Lin Ma, Bjorn Stenger, Wei Liu, Hongdong Li

To address this problem, we propose a new method which combines two GAN models, i. e., a learning-to-Blur GAN (BGAN) and learning-to-DeBlur GAN (DBGAN), in order to learn a better model for image deblurring by primarily learning how to blur images.

Deblurring Image Deblurring

Learning Classifiers on Positive and Unlabeled Data with Policy Gradient

1 code implementation15 Oct 2019 Tianyu Li, Chien-Chih Wang, Yukun Ma, Patricia Ortal, Qifang Zhao, Bjorn Stenger, Yu Hirate

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 classification model.

General Classification Reinforcement Learning

Deep Heterogeneous Autoencoders for Collaborative Filtering

no code implementations17 Dec 2018 Tianyu Li, Yukun Ma, Jiu Xu, Bjorn Stenger, Chen Liu, Yu Hirate

This paper leverages heterogeneous auxiliary information to address the data sparsity problem of recommender systems.

Collaborative Filtering Recommendation Systems

RGB-based 3D Hand Pose Estimation via Privileged Learning with Depth Images

no code implementations18 Nov 2018 Shanxin Yuan, Bjorn Stenger, Tae-Kyun Kim

We explore different ways of using this privileged information: (1) using depth data to initially train a depth-based network, (2) using the features from the depth-based network of the paired depth images to constrain mid-level RGB network weights, and (3) using the foreground mask, obtained from the depth data, to suppress the responses from the background area.

3D Hand Pose Estimation

Pano2CAD: Room Layout From A Single Panorama Image

no code implementations29 Sep 2016 Jiu Xu, Bjorn Stenger, Tommi Kerola, Tony Tung

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.

Bayesian Inference Object +4

Human Body Shape Estimation Using a Multi-Resolution Manifold Forest

no code implementations CVPR 2014 Frank Perbet, Sam Johnson, Minh-Tri Pham, Bjorn Stenger

This paper proposes a method for estimating the 3D body shape of a person with robustness to clothing.

valid

Bi-label Propagation for Generic Multiple Object Tracking

no code implementations CVPR 2014 Wenhan Luo, Tae-Kyun Kim, Bjorn Stenger, Xiaowei Zhao, Roberto Cipolla

In this paper, we propose a label propagation framework to handle the multiple object tracking (MOT) problem for a generic object type (cf.

Multiple Object Tracking Object

Expressive Visual Text-to-Speech Using Active Appearance Models

no code implementations CVPR 2013 Robert Anderson, Bjorn Stenger, Vincent Wan, Roberto Cipolla

This paper presents a complete system for expressive visual text-to-speech (VTTS), which is capable of producing expressive output, in the form of a 'talking head', given an input text and a set of continuous expression weights.

Text to Speech

Cannot find the paper you are looking for? You can Submit a new open access paper.