153 citations · 600 across the 23 of their papers we have counts for
23 papers
Speed Co-Augmentation for Unsupervised Audio-Visual Pre-training
Jiangliu Wang, Jianbo Jiao, Yibing Song +5
This work aims to improve unsupervised audio-visual pre-training. Inspired by the efficacy of data augmentation in visual contrastive learning, we propose a novel speed co-augmenta…
Revisiting Implicit Neural Representations in Low-Level Vision
Wentian Xu, Jianbo Jiao
Implicit Neural Representation (INR) has been emerging in computer vision in recent years. It has been shown to be effective in parameterising continuous signals such as dense 3D m…
FreMIM: Fourier Transform Meets Masked Image Modeling for Medical Image Segmentation
Wenxuan Wang, Jing Wang, Chen Chen +4
The research community has witnessed the powerful potential of self-supervised Masked Image Modeling (MIM), which enables the models capable of learning visual representation from…
Disentangled Pre-training for Image Matting
Yanda Li, Zilong Huang, Gang Yu +3
Image matting requires high-quality pixel-level human annotations to support the training of a deep model in recent literature. Whereas such annotation is costly and hard to scale,…
Mining Unseen Classes via Regional Objectness: A Simple Baseline for Incremental Segmentation
Zekang Zhang, Guangyu Gao, Zhiyuan Fang +2
Incremental or continual learning has been extensively studied for image classification tasks to alleviate catastrophic forgetting, a phenomenon that earlier learned knowledge is f…
Anatomy-Aware Contrastive Representation Learning for Fetal Ultrasound
Zeyu Fu, Jianbo Jiao, Robail Yasrab +3
Self-supervised contrastive representation learning offers the advantage of learning meaningful visual representations from unlabeled medical datasets for transfer learning. Howeve…
Quantised Transforming Auto-Encoders: Achieving Equivariance to Arbitrary Transformations in Deep Networks
Jianbo Jiao, João F. Henriques
In this work we investigate how to achieve equivariance to input transformations in deep networks, purely from data, without being given a model of those transformations. Convoluti…
Revitalizing CNN Attentions via Transformers in Self-Supervised Visual Representation Learning
Chongjian Ge, Youwei Liang, Yibing Song +3
Studies on self-supervised visual representation learning (SSL) improve encoder backbones to discriminate training samples without labels. While CNN encoders via SSL achieve compar…
Facial Anatomical Landmark Detection using Regularized Transfer Learning with Application to Fetal Alcohol Syndrome Recognition
Zeyu Fu, Jianbo Jiao, Michael Suttie +1
Fetal alcohol syndrome (FAS) caused by prenatal alcohol exposure can result in a series of cranio-facial anomalies, and behavioral and neurocognitive problems. Current diagnosis of…
Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation
Bingfeng Zhang, Jimin Xiao, Jianbo Jiao +2
Weakly supervised semantic segmentation is receiving great attention due to its low human annotation cost. In this paper, we aim to tackle bounding box supervised semantic segmenta…
Cross-Task Representation Learning for Anatomical Landmark Detection
Zeyu Fu, Jianbo Jiao, Michael Suttie +1
Recently, there is an increasing demand for automatically detecting anatomical landmarks which provide rich structural information to facilitate subsequent medical image analysis.…
Self-supervised Video Representation Learning by Pace Prediction
Jiangliu Wang, Jianbo Jiao, Yun-Hui Liu
This paper addresses the problem of self-supervised video representation learning from a new perspective -- by video pace prediction. It stems from the observation that human visua…
Self-Supervised Ultrasound to MRI Fetal Brain Image Synthesis
Jianbo Jiao, Ana I. L. Namburete, Aris T. Papageorghiou +1
Fetal brain magnetic resonance imaging (MRI) offers exquisite images of the developing brain but is not suitable for second-trimester anomaly screening, for which ultrasound (US) i…
Self-supervised Contrastive Video-Speech Representation Learning for Ultrasound
Jianbo Jiao, Yifan Cai, Mohammad Alsharid +3
In medical imaging, manual annotations can be expensive to acquire and sometimes infeasible to access, making conventional deep learning-based models difficult to scale. As a resul…
Self-supervised Video Representation Learning by Uncovering Spatio-temporal Statistics
Jiangliu Wang, Jianbo Jiao, Linchao Bao +3
This paper proposes a novel pretext task to address the self-supervised video representation learning problem. Specifically, given an unlabeled video clip, we compute a series of s…
Laplacian Denoising Autoencoder
Jianbo Jiao, Linchao Bao, Yunchao Wei +4
While deep neural networks have been shown to perform remarkably well in many machine learning tasks, labeling a large amount of ground truth data for supervised training is usuall…
Unified Image and Video Saliency Modeling
Richard Droste, Jianbo Jiao, J. Alison Noble
Visual saliency modeling for images and videos is treated as two independent tasks in recent computer vision literature. While image saliency modeling is a well-studied problem and…
Self-supervised Representation Learning for Ultrasound Video
Jianbo Jiao, Richard Droste, Lior Drukker +2
Recent advances in deep learning have achieved promising performance for medical image analysis, while in most cases ground-truth annotations from human experts are necessary to tr…
Anatomy-Aware Self-supervised Fetal MRI Synthesis from Unpaired Ultrasound Images
Jianbo Jiao, Ana I. L. Namburete, Aris T. Papageorghiou +1
Fetal brain magnetic resonance imaging (MRI) offers exquisite images of the developing brain but is not suitable for anomaly screening. For this ultrasound (US) is employed. While…
Self-supervised Spatio-temporal Representation Learning for Videos by Predicting Motion and Appearance Statistics
Jiangliu Wang, Jianbo Jiao, Linchao Bao +3
We address the problem of video representation learning without human-annotated labels. While previous efforts address the problem by designing novel self-supervised tasks using vi…
When AWGN-based Denoiser Meets Real Noises
Yuqian Zhou, Jianbo Jiao, Haibin Huang +4
Discriminative learning-based image denoisers have achieved promising performance on synthetic noises such as Additive White Gaussian Noise (AWGN). The synthetic noises adopted in…
Connecting Image Denoising and High-Level Vision Tasks via Deep Learning
Ding Liu, Bihan Wen, Jianbo Jiao +3
Image denoising and high-level vision tasks are usually handled independently in the conventional practice of computer vision, and their connection is fragile. In this paper, we co…
3D Hand Pose Tracking and Estimation Using Stereo Matching
Jiawei Zhang, Jianbo Jiao, Mingliang Chen +3
3D hand pose tracking/estimation will be very important in the next generation of human-computer interaction. Most of the currently available algorithms rely on low-cost active dep…