Search Results for author: Jia-Wei Chen

Found 15 papers, 3 papers with code

Self-Supervised CycleGAN for Object-Preserving Image-to-Image Domain Adaptation

no code implementations ECCV 2020 Xinpeng Xie, Jia-Wei Chen, Yuexiang Li, Linlin Shen, Kai Ma, Yefeng Zheng

Recent generative adversarial network (GAN) based methods (e. g., CycleGAN) are prone to fail at preserving image-objects in image-to-image translation, which reduces their practicality on tasks such as domain adaptation.

Domain Adaptation Image-to-Image Translation +2

DPGEN: Differentially Private Generative Energy-Guided Network for Natural Image Synthesis

no code implementations CVPR 2022 Jia-Wei Chen, Chia-Mu Yu, Ching-Chia Kao, Tzai-Wei Pang, Chun-Shien Lu

Despite an increased demand for valuable data, the privacy concerns associated with sensitive datasets present a barrier to data sharing.

Image Generation

MI^2GAN: Generative Adversarial Network for Medical Image Domain Adaptation using Mutual Information Constraint

no code implementations22 Jul 2020 Xinpeng Xie, Jia-Wei Chen, Yuexiang Li, Linlin Shen, Kai Ma, Yefeng Zheng

Domain shift between medical images from multicentres is still an open question for the community, which degrades the generalization performance of deep learning models.

Domain Adaptation Translation

Instance-aware Self-supervised Learning for Nuclei Segmentation

no code implementations22 Jul 2020 Xinpeng Xie, Jia-Wei Chen, Yuexiang Li, Linlin Shen, Kai Ma, Yefeng Zheng

Due to the wide existence and large morphological variances of nuclei, accurate nuclei instance segmentation is still one of the most challenging tasks in computational pathology.

Instance Segmentation Self-Supervised Learning +1

Self-Loop Uncertainty: A Novel Pseudo-Label for Semi-Supervised Medical Image Segmentation

no code implementations20 Jul 2020 Yuexiang Li, Jia-Wei Chen, Xinpeng Xie, Kai Ma, Yefeng Zheng

A novel pseudo-label (namely self-loop uncertainty), generated by recurrently optimizing the neural network with a self-supervised task, is adopted as the ground-truth for the unlabeled images to augment the training set and boost the segmentation accuracy.

Image Segmentation pseudo label +2

A Convolutional Neural Network with Parallel Multi-Scale Spatial Pooling to Detect Temporal Changes in SAR Images

no code implementations22 May 2020 Jia-Wei Chen, Rongfang Wang, Fan Ding, Bo Liu, Licheng Jiao, Jie Zhang

Furthermore, to verify the generalization of the proposed method, we apply our proposed method to the cross-dataset bitemporal SAR image change detection, where the MSSP network (MSSP-Net) is trained on a dataset and then applied to an unknown testing dataset.

Change Detection

VAE/WGAN-Based Image Representation Learning For Pose-Preserving Seamless Identity Replacement In Facial Images

no code implementations2 Mar 2020 Hiroki Kawai, Jia-Wei Chen, Prakash Ishwar, Janusz Konrad

We present a novel variational generative adversarial network (VGAN) based on Wasserstein loss to learn a latent representation from a face image that is invariant to identity but preserves head-pose information.

Representation Learning

Sams-Net: A Sliced Attention-based Neural Network for Music Source Separation

1 code implementation12 Sep 2019 Tingle Li, Jia-Wei Chen, Haowen Hou, Ming Li

Convolutional Neural Network (CNN) or Long short-term memory (LSTM) based models with the input of spectrogram or waveforms are commonly used for deep learning based audio source separation.

Audio Source Separation Music Source Separation

SAR Image Change Detection via Spatial Metric Learning with an Improved Mahalanobis Distance

no code implementations19 Jun 2019 Rongfang Wang, Jia-Wei Chen, Yule Wang, Licheng Jiao, Mi Wang

In this letter, we proposed a spatial metric learning method to obtain a difference image more robust to the speckle by learning a metric from a set of constraint pairs.

Change Detection Metric Learning

OctopusNet: A Deep Learning Segmentation Network for Multi-modal Medical Images

no code implementations5 Jun 2019 Yu Chen, Jia-Wei Chen, Dong Wei, Yuexiang Li, Yefeng Zheng

Two approaches are widely used in the literature to fuse multiple modalities in the segmentation networks: early-fusion (which stacks multiple modalities as different input channels) and late-fusion (which fuses the segmentation results from different modalities at the very end).

HAHE: Hierarchical Attentive Heterogeneous Information Network Embedding

3 code implementations31 Jan 2019 Sheng Zhou, Jiajun Bu, Xin Wang, Jia-Wei Chen, Can Wang

Second, given a meta path, nodes in HIN are connected by path instances while existing works fail to fully explore the differences between path instances that reflect nodes' preferences in the semantic space.

Network Embedding

Image Blind Denoising With Generative Adversarial Network Based Noise Modeling

no code implementations CVPR 2018 Jingwen Chen, Jia-Wei Chen, Hongyang Chao, Ming Yang

In this paper, we consider a typical image blind denoising problem, which is to remove unknown noise from noisy images.


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