Search Results for author: Jianbo Jiao

Found 35 papers, 17 papers with code

Multi-view Self-supervised Disentanglement for General Image Denoising

1 code implementation ICCV 2023 Hao Chen, Chenyuan Qu, Yu Zhang, Chen Chen, Jianbo Jiao

It is understandable as the model is designed to learn paired mapping (e. g. from a noisy image to its clean version).

Disentanglement Image Denoising +1

Med-Tuning: Exploring Parameter-Efficient Transfer Learning for Medical Volumetric Segmentation

no code implementations21 Apr 2023 Wenxuan Wang, Jiachen Shen, Chen Chen, Jianbo Jiao, Yan Zhang, Shanshan Song, Jiangyun Li

Deep learning based medical volumetric segmentation methods either train the model from scratch or follow the standard "pre-training then finetuning" paradigm.

Transfer Learning

FreMIM: Fourier Transform Meets Masked Image Modeling for Medical Image Segmentation

no code implementations21 Apr 2023 Wenxuan Wang, Jing Wang, Chen Chen, Jianbo Jiao, Lichao Sun, Yuanxiu Cai, Shanshan Song, Jiangyun Li

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 unlabeled data. In this paper, to incorporate both the crucial global structural information and local details for dense prediction tasks, we alter the perspective to the frequency domain and present a new MIM-based framework named FreMIM for self-supervised pre-training to better accomplish medical image segmentation task.

Image Segmentation Medical Image Segmentation +2

Revisiting Implicit Neural Representations in Low-Level Vision

1 code implementation20 Apr 2023 Wentian Xu, Jianbo Jiao

Implicit Neural Representation (INR) has been emerging in computer vision in recent years.

Deblurring Image Denoising +2

Disentangled Pre-training for Image Matting

no code implementations3 Apr 2023 Yanda Li, Zilong Huang, Gang Yu, Ling Chen, Yunchao Wei, Jianbo Jiao

The pre-training task is designed in a similar manner as image matting, where random trimap and alpha matte are generated to achieve an image disentanglement objective.

Disentanglement Image Matting

CoinSeg: Contrast Inter- and Intra- Class Representations for Incremental Segmentation

no code implementations ICCV 2023 Zekang Zhang, Guangyu Gao, Jianbo Jiao, Chi Harold Liu, Yunchao Wei

Therefore, we prioritize the model's plasticity and propose the Contrast inter- and intra-class representations for Incremental Segmentation (CoinSeg), which pursue discriminative representations for flexible parameter tuning.

Class-Incremental Semantic Segmentation

Diffuse3D: Wide-Angle 3D Photography via Bilateral Diffusion

1 code implementation ICCV 2023 Yutao Jiang, Yang Zhou, Yuan Liang, Wenxi Liu, Jianbo Jiao, Yuhui Quan, Shengfeng He

To address the above issues, we propose Diffuse3D which employs a pre-trained diffusion model for global synthesis, while amending the model to activate depth-aware inference.

Denoising Novel View Synthesis

CL-MVSNet: Unsupervised Multi-View Stereo with Dual-Level Contrastive Learning

no code implementations ICCV 2023 Kaiqiang Xiong, Rui Peng, Zhe Zhang, Tianxing Feng, Jianbo Jiao, Feng Gao, Ronggang Wang

On the one hand, we present an image-level contrastive branch to guide the model to acquire more context awareness, thus leading to more complete depth estimation in indistinguishable regions.

Contrastive Learning Depth Estimation

Mining Unseen Classes via Regional Objectness: A Simple Baseline for Incremental Segmentation

1 code implementation13 Nov 2022 Zekang Zhang, Guangyu Gao, Zhiyuan Fang, Jianbo Jiao, Yunchao Wei

Our MicroSeg is based on the assumption that background regions with strong objectness possibly belong to those concepts in the historical or future stages.

Class-Incremental Semantic Segmentation Continual Learning +1

Anatomy-Aware Contrastive Representation Learning for Fetal Ultrasound

1 code implementation22 Aug 2022 Zeyu Fu, Jianbo Jiao, Robail Yasrab, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble

The proposed approach is demonstrated for automated fetal ultrasound imaging tasks, enabling the positive pairs from the same or different ultrasound scans that are anatomically similar to be pulled together and thus improving the representation learning.

Anatomy Contrastive Learning +2

Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning

1 code implementation NeurIPS 2021 Chongjian Ge, Youwei Liang, Yibing Song, Jianbo Jiao, Jue Wang, Ping Luo

Motivated by the transformers that explore visual attention effectively in recognition scenarios, we propose a CNN Attention REvitalization (CARE) framework to train attentive CNN encoders guided by transformers in SSL.

Image Classification object-detection +3

Quantised Transforming Auto-Encoders: Achieving Equivariance to Arbitrary Transformations in Deep Networks

no code implementations25 Nov 2021 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.

Pose Estimation Translation

Revitalizing CNN Attentions via Transformers in Self-Supervised Visual Representation Learning

1 code implementation11 Oct 2021 Chongjian Ge, Youwei Liang, Yibing Song, Jianbo Jiao, Jue Wang, Ping Luo

Motivated by the transformers that explore visual attention effectively in recognition scenarios, we propose a CNN Attention REvitalization (CARE) framework to train attentive CNN encoders guided by transformers in SSL.

Image Classification object-detection +3

Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation

1 code implementation8 Jun 2021 Bingfeng Zhang, Jimin Xiao, Jianbo Jiao, Yunchao Wei, Yao Zhao

More importantly, our approach can be readily applied to bounding box supervised instance segmentation task or other weakly supervised semantic segmentation tasks, with state-of-the-art or comparable performance among almot all weakly supervised tasks on PASCAL VOC or COCO dataset.

Box-supervised Instance Segmentation Model Optimization +2

Scene Context-Aware Salient Object Detection

1 code implementation ICCV 2021 Avishek Siris, Jianbo Jiao, Gary K.L. Tam, Xianghua Xie, Rynson W.H. Lau

To our knowledge, such high-level semantic contextual information of image scenes is under-explored for saliency detection in the literature.

object-detection Object Detection +2

Cross-Task Representation Learning for Anatomical Landmark Detection

no code implementations28 Sep 2020 Zeyu Fu, Jianbo Jiao, Michael Suttie, J. Alison Noble

The main idea of the proposed method is to retain the feature representations of the source model on the target task data, and to leverage them as an additional source of supervisory signals for regularizing the target model learning, thereby improving its performance under limited training samples.

Face Recognition Representation Learning +1

Self-supervised Video Representation Learning by Uncovering Spatio-temporal Statistics

2 code implementations31 Aug 2020 Jiangliu Wang, Jianbo Jiao, Linchao Bao, Shengfeng He, Wei Liu, Yun-hui Liu

Specifically, given an unlabeled video clip, we compute a series of spatio-temporal statistical summaries, such as the spatial location and dominant direction of the largest motion, the spatial location and dominant color of the largest color diversity along the temporal axis, etc.

Action Recognition Representation Learning +3

Self-Supervised Ultrasound to MRI Fetal Brain Image Synthesis

1 code implementation19 Aug 2020 Jianbo Jiao, Ana I. L. Namburete, Aris T. Papageorghiou, J. Alison Noble

To regularise the anatomical structures between US and MRI during synthesis, we further propose an adversarial structural constraint.

Image Generation

Self-supervised Contrastive Video-Speech Representation Learning for Ultrasound

no code implementations14 Aug 2020 Jianbo Jiao, Yifan Cai, Mohammad Alsharid, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble

For this case, we assume that there is a high correlation between the ultrasound video and the corresponding narrative speech audio of the sonographer.

Contrastive Learning Gaze Prediction +1

Self-supervised Video Representation Learning by Pace Prediction

1 code implementation ECCV 2020 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.

Action Recognition Contrastive Learning +3

Referring Image Segmentation by Generative Adversarial Learning

no code implementations IEEE 2020 Shuang Qiu, Yao Zhao, Jianbo Jiao, Yunchao Wei, Shikui Wei

To this end, we propose to train the referring image segmentation model in a generative adversarial fashion, which well addresses the distribution similarity problem.

Image Segmentation Referring Expression +2

Laplacian Denoising Autoencoder

no code implementations30 Mar 2020 Jianbo Jiao, Linchao Bao, Yunchao Wei, Shengfeng He, Honghui Shi, Rynson Lau, Thomas S. Huang

This can be naturally generalized to span multiple scales with a Laplacian pyramid representation of the input data.

Denoising Self-Supervised Learning

Unified Image and Video Saliency Modeling

2 code implementations ECCV 2020 Richard Droste, Jianbo Jiao, J. Alison Noble

We evaluate our method on the video saliency datasets DHF1K, Hollywood-2 and UCF-Sports, and the image saliency datasets SALICON and MIT300.

Domain Adaptation Saliency Prediction

Anatomy-Aware Self-supervised Fetal MRI Synthesis from Unpaired Ultrasound Images

no code implementations8 Sep 2019 Jianbo Jiao, Ana I. L. Namburete, Aris T. Papageorghiou, J. Alison Noble

The feasibility of the approach to produce realistic looking MR images is demonstrated quantitatively and with a qualitative evaluation compared to real fetal MR images.


Geometry-Aware Distillation for Indoor Semantic Segmentation

1 code implementation CVPR 2019 Jianbo Jiao, Yunchao Wei, Zequn Jie, Honghui Shi, Rynson W.H. Lau, Thomas S. Huang

It has been shown that jointly reasoning the 2D appearance and 3D information from RGB-D domains is beneficial to indoor scene semantic segmentation.

Semantic Segmentation

When AWGN-based Denoiser Meets Real Noises

2 code implementations6 Apr 2019 Yuqian Zhou, Jianbo Jiao, Haibin Huang, Yang Wang, Jue Wang, Honghui Shi, Thomas Huang

In this paper, we propose a novel approach to boost the performance of a real image denoiser which is trained only with synthetic pixel-independent noise data dominated by AWGN.


Connecting Image Denoising and High-Level Vision Tasks via Deep Learning

1 code implementation6 Sep 2018 Ding Liu, Bihan Wen, Jianbo Jiao, Xian-Ming Liu, Zhangyang Wang, Thomas S. Huang

Second we propose a deep neural network solution that cascades two modules for image denoising and various high-level tasks, respectively, and use the joint loss for updating only the denoising network via back-propagation.

Image Denoising Vocal Bursts Intensity Prediction

Task-driven Webpage Saliency

no code implementations ECCV 2018 Quanlong Zheng, Jianbo Jiao, Ying Cao, Rynson W. H. Lau

Inspired by the observation that given a specific task, human attention is strongly correlated with certain semantic components on a webpage (e. g., images, buttons and input boxes), our network explicitly disentangles saliency prediction into two independent sub-tasks: task-specific attention shift prediction and task-free saliency prediction.

Saliency Prediction

Delving Into Salient Object Subitizing and Detection

no code implementations ICCV 2017 Shengfeng He, Jianbo Jiao, Xiaodan Zhang, Guoqiang Han, Rynson W. H. Lau

Experiments show that the proposed multi-task network outperforms existing multi-task architectures, and the auxiliary subitizing network provides strong guidance to salient object detection by reducing false positives and producing coherent saliency maps.

object-detection RGB Salient Object Detection +1

3D Hand Pose Tracking and Estimation Using Stereo Matching

no code implementations23 Oct 2016 Jiawei Zhang, Jianbo Jiao, Mingliang Chen, Liangqiong Qu, Xiaobin Xu, Qingxiong Yang

This paper demonstrates that the performance of the state-of-the art tracking/estimation algorithms can be maintained with most stereo matching algorithms on the proposed benchmark, as long as the hand segmentation is correct.

Hand Segmentation Pose Tracking +2

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