Search Results for author: Yaohua Liu

Found 15 papers, 3 papers with code

Learn from the Past: A Proxy based Adversarial Defense Framework to Boost Robustness

no code implementations19 Oct 2023 Yaohua Liu, Jiaxin Gao, Zhu Liu, Xianghao Jiao, Xin Fan, Risheng Liu

In light of the vulnerability of deep learning models to adversarial samples and the ensuing security issues, a range of methods, including Adversarial Training (AT) as a prominent representative, aimed at enhancing model robustness against various adversarial attacks, have seen rapid development.

Adversarial Defense

Diving into Darkness: A Dual-Modulated Framework for High-Fidelity Super-Resolution in Ultra-Dark Environments

no code implementations11 Sep 2023 Jiaxin Gao, Ziyu Yue, Yaohua Liu, Sihan Xie, Xin Fan, Risheng Liu

Super-resolution tasks oriented to images captured in ultra-dark environments is a practical yet challenging problem that has received little attention.


PEARL: Preprocessing Enhanced Adversarial Robust Learning of Image Deraining for Semantic Segmentation

no code implementations25 May 2023 Xianghao Jiao, Yaohua Liu, Jiaxin Gao, Xinyuan Chu, Risheng Liu, Xin Fan

In light of the significant progress made in the development and application of semantic segmentation tasks, there has been increasing attention towards improving the robustness of segmentation models against natural degradation factors (e. g., rain streaks) or artificially attack factors (e. g., adversarial attack).

Adversarial Attack Rain Removal +2

Motion-Scenario Decoupling for Rat-Aware Video Position Prediction: Strategy and Benchmark

no code implementations17 May 2023 Xiaofeng Liu, Jiaxin Gao, Yaohua Liu, Risheng Liu, Nenggan Zheng

Recently significant progress has been made in human action recognition and behavior prediction using deep learning techniques, leading to improved vision-based semantic understanding.

Action Recognition motion prediction +3

Averaged Method of Multipliers for Bi-Level Optimization without Lower-Level Strong Convexity

1 code implementation7 Feb 2023 Risheng Liu, Yaohua Liu, Wei Yao, Shangzhi Zeng, Jin Zhang

Gradient methods have become mainstream techniques for Bi-Level Optimization (BLO) in learning fields.

Efficient Cavity Searching for Gene Network of Influenza A Virus

no code implementations5 Nov 2022 Junjie Li, Jietong Zhao, Yanqing Su, Jiahao Shen, Yaohua Liu, Xinyue Fan, Zheng Kou

High order structures (cavities and cliques) of the gene network of influenza A virus reveal tight associations among viruses during evolution and are key signals that indicate viral cross-species infection and cause pandemics.


LGC-Net: A Lightweight Gyroscope Calibration Network for Efficient Attitude Estimation

no code implementations19 Sep 2022 Yaohua Liu, Wei Liang, Jinqiang Cui

This paper presents a lightweight, efficient calibration neural network model for denoising low-cost microelectromechanical system (MEMS) gyroscope and estimating the attitude of a robot in real-time.


Triple-level Model Inferred Collaborative Network Architecture for Video Deraining

no code implementations8 Nov 2021 Pan Mu, Zhu Liu, Yaohua Liu, Risheng Liu, Xin Fan

In this paper, we develop a model-guided triple-level optimization framework to deduce network architecture with cooperating optimization and auto-searching mechanism, named Triple-level Model Inferred Cooperating Searching (TMICS), for dealing with various video rain circumstances.

Optical Flow Estimation Rain Removal

Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond

1 code implementation NeurIPS 2021 Risheng Liu, Yaohua Liu, Shangzhi Zeng, Jin Zhang

In particular, by introducing an auxiliary as initialization to guide the optimization dynamics and designing a pessimistic trajectory truncation operation, we construct a reliable approximate version of the original BLO in the absence of LLC hypothesis.

Bilevel Optimization

Field-induced intermediate ordered phase and anisotropic interlayer interactions in $α$-RuCl$_3$

no code implementations30 Dec 2020 Christian Balz, Lukas Janssen, Paula Lampen-Kelley, Arnab Banerjee, Yaohua Liu, Jiaqiang Yan, David Mandrus, Matthias Vojta, Stephen E. Nagler

In $\alpha$-RuCl$_3$, an external magnetic field applied within the honeycomb plane can induce a transition from a magnetically ordered state to a disordered state that is potentially related to the Kitaev quantum spin liquid.

Strongly Correlated Electrons Materials Science

BOML: A Modularized Bilevel Optimization Library in Python for Meta Learning

2 code implementations28 Sep 2020 Yaohua Liu, Risheng Liu

learning to learn) has recently emerged as a promising paradigm for a variety of applications.

Bilevel Optimization Meta-Learning

Communication-Censored Linearized ADMM for Decentralized Consensus Optimization

no code implementations15 Sep 2019 Weiyu Li, Yaohua Liu, Zhi Tian, Qing Ling

COLA is proven to be convergent when the local cost functions have Lipschitz continuous gradients and the censoring threshold is summable.


Discovering Features in Sr$_{14}$Cu$_{24}$O$_{41}$ Neutron Single Crystal Diffraction Data by Cluster Analysis

no code implementations13 Sep 2018 Yawei Hui, Yaohua Liu, Byung-Hoon Park

To address the SMC'18 data challenge, "Discovering Features in Sr$_{14}$Cu$_{24}$O$_{41}$", we have used the clustering algorithm "DBSCAN" to separate the diffuse scattering features from the Bragg peaks, which takes into account both spatial and photometric information in the dataset during in the clustering process.

Clustering Open-Ended Question Answering

Computer Vision-aided Atom Tracking in STEM Imaging

no code implementations13 Sep 2018 Yawei Hui, Yaohua Liu

To address the SMC'17 data challenge -- "Data mining atomically resolved images for material properties", we first used the classic "blob detection" algorithms developed in computer vision to identify all atom centers in each STEM image frame.

Volumetric Data Exploration with Machine Learning-Aided Visualization in Neutron Science

no code implementations16 Oct 2017 Yawei Hui, Yaohua Liu

Recent advancements in neutron and X-ray sources, instrumentation and data collection modes have significantly increased the experimental data size (which could easily contain 10$^{8}$ -- 10$^{10}$ data points), so that conventional volumetric visualization approaches become inefficient for both still imaging and interactive OpenGL rendition in a 3D setting.

BIG-bench Machine Learning Boundary Detection +1

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