Search Results for author: Jingyang Zhang

Found 17 papers, 10 papers with code

NeILF: Neural Incident Light Field for Physically-based Material Estimation

no code implementations14 Mar 2022 Yao Yao, Jingyang Zhang, Jingbo Liu, Yihang Qu, Tian Fang, David McKinnon, Yanghai Tsin, Long Quan

We present a differentiable rendering framework for material and lighting estimation from multi-view images and a reconstructed geometry.

Privacy Leakage of Adversarial Training Models in Federated Learning Systems

1 code implementation21 Feb 2022 Jingyang Zhang, Yiran Chen, Hai Li

Adversarial Training (AT) is crucial for obtaining deep neural networks that are robust to adversarial attacks, yet recent works found that it could also make models more vulnerable to privacy attacks.

Federated Learning

Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation

1 code implementation18 Sep 2021 Ran Gu, Jingyang Zhang, Rui Huang, Wenhui Lei, Guotai Wang, Shaoting Zhang

First, we present a domain composition method that represents one certain domain by a linear combination of a set of basis representations (i. e., a representation bank).

Domain Generalization Medical Image Segmentation +1

Learning Signed Distance Field for Multi-view Surface Reconstruction

1 code implementation ICCV 2021 Jingyang Zhang, Yao Yao, Long Quan

In this work, we introduce a novel neural surface reconstruction framework that leverages the knowledge of stereo matching and feature consistency to optimize the implicit surface representation.

Stereo Matching Surface Reconstruction

Mixture Outlier Exposure: Towards Out-of-Distribution Detection in Fine-grained Environments

1 code implementation7 Jun 2021 Jingyang Zhang, Nathan Inkawhich, Randolph Linderman, Yiran Chen, Hai Li

We then propose Mixture Outlier Exposure (MixOE), which mixes ID data and training outliers to expand the coverage of different OOD granularities, and trains the model such that the prediction confidence linearly decays as the input transitions from ID to OOD.

OOD Detection Out-of-Distribution Detection

SS-CADA: A Semi-Supervised Cross-Anatomy Domain Adaptation for Coronary Artery Segmentation

no code implementations6 May 2021 Jingyang Zhang, Ran Gu, Guotai Wang, Hongzhi Xie, Lixu Gu

To solve this problem, we propose a Semi-Supervised Cross-Anatomy Domain Adaptation (SS-CADA) which requires only limited annotations for coronary arteries in XAs.

Domain Adaptation

MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning

1 code implementation25 Apr 2021 Xiangde Luo, Guotai Wang, Tao Song, Jingyang Zhang, Michael Aertsen, Jan Deprest, Sebastien Ourselin, Tom Vercauteren, Shaoting Zhang

To solve these problems, we propose a novel deep learning-based interactive segmentation method that not only has high efficiency due to only requiring clicks as user inputs but also generalizes well to a range of previously unseen objects.

Interactive Segmentation Medical Image Segmentation +1

Can Targeted Adversarial Examples Transfer When the Source and Target Models Have No Label Space Overlap?

no code implementations17 Mar 2021 Nathan Inkawhich, Kevin J Liang, Jingyang Zhang, Huanrui Yang, Hai Li, Yiran Chen

During the online phase of the attack, we then leverage representations of highly related proxy classes from the whitebox distribution to fool the blackbox model into predicting the desired target class.

Visibility-aware Multi-view Stereo Network

1 code implementation18 Aug 2020 Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang

As such, the adverse influence of occluded pixels is suppressed in the cost fusion.

3D Reconstruction Depth Estimation +1

Learning Stereo Matchability in Disparity Regression Networks

1 code implementation11 Aug 2020 Jingyang Zhang, Yao Yao, Zixin Luo, Shiwei Li, Tianwei Shen, Tian Fang, Long Quan

Finally, a matchability-aware disparity refinement is introduced to improve the depth inference in weakly matchable regions.

Stereo Disparity Estimation Stereo Matching

Weakly Supervised Vessel Segmentation in X-ray Angiograms by Self-Paced Learning from Noisy Labels with Suggestive Annotation

no code implementations27 May 2020 Jingyang Zhang, Guotai Wang, Hongzhi Xie, Shuyang Zhang, Ning Huang, Shaoting Zhang, Lixu Gu

The segmentation of coronary arteries in X-ray angiograms by convolutional neural networks (CNNs) is promising yet limited by the requirement of precisely annotating all pixels in a large number of training images, which is extremely labor-intensive especially for complex coronary trees.

BlendedMVS: A Large-scale Dataset for Generalized Multi-view Stereo Networks

2 code implementations CVPR 2020 Yao Yao, Zixin Luo, Shiwei Li, Jingyang Zhang, Yufan Ren, Lei Zhou, Tian Fang, Long Quan

Compared with other computer vision tasks, it is rather difficult to collect a large-scale MVS dataset as it requires expensive active scanners and labor-intensive process to obtain ground truth 3D structures.

3D Reconstruction

Exploring Bit-Slice Sparsity in Deep Neural Networks for Efficient ReRAM-Based Deployment

1 code implementation18 Sep 2019 Jingyang Zhang, Huanrui Yang, Fan Chen, Yitu Wang, Hai Li

However, the power hungry analog-to-digital converters (ADCs) prevent the practical deployment of ReRAM-based DNN accelerators on end devices with limited chip area and power budget.

A novel active learning framework for classification: using weighted rank aggregation to achieve multiple query criteria

no code implementations27 Sep 2018 Yu Zhao, Zhenhui Shi, Jingyang Zhang, Dong Chen, Lixu Gu

The proposed method serves as a heuristic means to select high-value samples of high scalability and generality and is implemented through a three-step process: (1) the transformation of the sample selection to sample ranking and scoring, (2) the computation of the self-adaptive weights of each criterion, and (3) the weighted aggregation of each sample rank list.

Active Learning General Classification

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