ECCV 2020 的对抗相关论文(对抗生成、对抗攻击)

ECCV 2020 的对抗相关论文(对抗生成、对抗攻击)

点击上方机器学习与生成对抗网络”,关注”星标”

获取有趣、好玩的前沿干货!


ECCV 2020 的对抗相关论文(对抗生成、对抗攻击) 戳我,查看GAN的系列专辑~!



本文汇总了ECCV 2020上部分对抗相关论文,后续公众号会随缘对一些paper做解读。感兴趣的同学,可先自行根据标题,搜索对应链接(有些paper可能未公布)。值得注意的是,这里的对抗包括了生成对抗GAN、以及对抗攻击/防御,两者
概念上是迥然
的。




677
House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout Generation
Oral


2258
Regularization with Latent Space Virtual Adversarial Training
Oral


2307
Model-Agnostic Boundary-Adversarial Sampling for Test-Time Generalization in Few-Shot learning
Oral


3047
Multi-task Learning Increases Adversarial Robustness
Oral


3570
Towards Automated Testing and Robustification by Semantic Adversarial Data Generation
Oral


3582
Adversarial Generative Grammars for Human Activity Prediction
Oral


5932
TopoGAN: A Topology-Aware Generative Adversarial Network
Oral


1425
Studying the Transferability of Adversarial Attacks on Object DetectorsSpotlight
1915Multimodal Shape Completion via Conditional Generative Adversarial Networks
Spotlight


2390
CPGAN: Content-Parsing Generative Adversarial Networks for Text-to-Image Synthesis
Spotlight


4383
Adversarial T-shirt! Evading Person Detectors in A Physical World
Spotlight


4727
Counterfactual Vision-and-Language Navigation via Adversarial Path Sampler
Spotlight


123
Adversarial Self-Supervised Learning for Semi-Supervised 3D Action Recognition
Poster


457
Improved Adversarial Training via Learned Optimizer
Poster


634
Domain-Specific Mappings for Generative Adversarial Style Transfer
Poster


978
Unpaired Image-to-Image Translation using Adversarial Consistency Loss
Poster


984
Dual Adversarial Network: Toward Real Noise Removal and Noise Generation
Poster


1355
Adversarial Continual Learning
Poster


1456
Regional Homogeneity: Towards Learning Transferable Universal Adversarial Perturbations Against Defenses
Poster


1509
AMLN: Adversarial-based Mutual Learning Network for Online Knowledge Distillation
Poster


1541
AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds
Poster


1905
Bias-based Universal Adversarial Patch Attack for Automatic Check-out
Poster


2059
SemanticAdv: Generating Adversarial Examples via Attribute-conditioned Image Editing
Poster


2116
Symbiotic Adversarial Learning for Attribute-Based Person Search
Poster


2121
Adversarial Background-Aware Loss for Weakly-supervised Temporal Activity Localization
Poster


2160
Multi-level Wavelet-based Generative Adversarial Network for Perceptual Quality Enhancement of Compressed Video
Poster


2246
Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation
Poster


2274
Adversarial Ranking Attack and Defense
Poster


2336
Boosting Decision-based Black-box Adversarial Attacks with Random Sign Flip
Poster


2709
Design and Interpretation of Universal Adversarial Patches in Face Detection
Poster


2865
Open-set Adversarial Defense
Poster


3150
Robust Tracking against Adversarial Attacks
Poster


3245
Semantic Equivalent Adversarial Data Augmentation for Visual Question Answering
Poster


3307
Adversarial Semantic Data Augmentation for Human Pose Estimation
Poster


3412
Motion-Excited Sampler: Video Adversarial Attack with Sparked Prior
Poster


3627
Incorporating Reinforced Adversarial Learning in Autoregressive Image Generation
Poster


3632
APRICOT: A Dataset of Physical Adversarial Attacks on Object Detection
Poster


3902
S
parse Adversarial Attack via Perturbation Factorization
Poster


4118
Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting
Poster


4302
DeepLandscape: Adversarial Modeling of Landscape Videos
Poster


4334
Connecting the Dots: Detecting Adversarial Perturbations Using Context Inconsistency
Poster


4362
Square Attack: a query-efficient black-box adversarial attack via random search
Poster


4583
BIRNAT: Bidirectional Recurrent Neural Networks with Adversarial Training for Video Snapshot Compressive Imaging
Poster


4690
Mind the Discriminability: Asymmetric Adversarial Domain Adaptation
Poster


4757
Dual Adversarial Network for Deep Active Learning
Poster


4810
Adversarial Training with Bi-directional Likelihood Regularization for Visual Classification
Poster


4889
Improving Query Efficiency of Black-box Adversarial Attack
Poster


529
1
Efficient Adversarial Attacks for Visual Object Tracking
Poster


5331
Adversarial Robustness on In- and Out-Distribution Improves Explainability
Poster


5573
Multi-Source Open-Set Deep Adversarial Domain Adaptation
Poster


5686
Improving Adversarial Robustness by Enforcing Local and Global Compactness
Poster


5687
TopoGAN: A Generative Adversarial Approach to Topology-Aware Road Segmentation
Poster


5888
Discriminative Partial Domain Adversarial Network
Poster


6231
Unsupervised Monocular Depth Estimation for Night-time Images using Adversarial Domain Feature Adaptation
Poster


6438
Defense Against Adversarial Attacks via Controlling Gradient Leaking on Embedded Manifolds
Poster


6748
Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-Linear Activations
Poster


6753
Synthesizing Coupled 3D Face Modalities by Trunk-Branch Generative Adversarial Networks
Poster


6796
Dual Mixup Regularized Learning for Adversarial Domain Adaptation
Poster


6895
Adversarial Data Augmentation via Deformation Statistics
Poster


7451
Manifold Projection for Adversarial Defense on Face Recognition
Poster


猜您喜欢:

超100篇!CVPR 2020最全GAN论文梳理汇总!

拆解组新的GAN:解耦表征MixNMatch

StarGAN第2版:多域多样性图像生成

附下载 | 《可解释的机器学习》中文版

附下载 |《TensorFlow 2.0 深度学习算法实战》

附下载 |《计算机视觉中的数学方法》分享

《基于深度学习的表面缺陷检测方法综述》

《零样本图像分类综述: 十年进展》

《基于深度神经网络的少样本学习综述》

ECCV 2020 的对抗相关论文(对抗生成、对抗攻击)

版权声明:本文内容由互联网用户自发贡献,该文观点仅代表作者本人。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如发现本站有涉嫌侵权/违法违规的内容, 请联系我们举报,一经查实,本站将立刻删除。

发布者:全栈程序员-站长,转载请注明出处:https://javaforall.net/2505.html原文链接:https://javaforall.net

(0)
上一篇 2020年11月14日 上午11:06
下一篇 2020年11月14日 上午11:06


相关推荐

  • 打开文件句柄数 linux_linux文件句柄数量怎么看

    打开文件句柄数 linux_linux文件句柄数量怎么看Linux3.2.0-23-generic(linux)09/08/2014_x86_64_(8CPU)02:01:55PMdentunusdfile-nrinode-nrpty-nr02:02:05PM38465156825731402:02:15PM38465…

    2022年10月17日
    5
  • C语言和Java哪个难学?[通俗易懂]

    C语言和Java哪个难学?[通俗易懂]有人说:世界上有两种程序员,一种用Tab键,另一种用Space键。在程序员圈子有这样一条鄙视链(小道传说):C++程序员看不起C程序员,C程序员看不起Java程序员,Java程序员看不起C#程序员,C#程序员看不起美工。为什么大家普遍认为C语言比Java难?我认为原因如下:C属于底层代码,能窥探到底层,也就是说可以拿它写硬件驱动,学习C语言前面的内容比Java简单但是到了后来特别是指针、…

    2022年7月16日
    23
  • mybatis逆向工程是什么意思_长话短说的方法

    mybatis逆向工程是什么意思_长话短说的方法目录Mybatis逆向工程一、通过Eclipse插件完成Mybatis逆向工程1.在线安装Eclipse插件2.新建一个JavaProject项目3.编写配置文件4.使用插件运行二、通过Java代码完成Mybatis逆向工程1.新建一个JavaProject项目2.编写配置文件3.编写生成代码程序三、通过Maven完成Mybatis逆向工程1…

    2022年8月21日
    6
  • python hexdump_细说Linux中怎么用hexdump命令

    python hexdump_细说Linux中怎么用hexdump命令摘要:hexdump描述:hexdump命令一般用来查看”二进制”文件的十六进制编码,从手册上查看,其查看的内容还要很多,诸如:ascii,decimal,hexadecimal,octal参数:hexdump[-bcCdovx][-eformat_string][-fformat_file][-nlength][-sskip]file示例:新增一个文本文件,在test…

    2025年12月10日
    4
  • pagehelper,pageinfo用法[通俗易懂]

    pagehelper,pageinfo用法[通俗易懂]pagehelper,从pageinfo中取到的total不正确的处理。最近在使用pagehelper时遇到一些问题。2个类似的查询都用的PageHelper.startPage进行分页,A方法pageinfo中取出来的total,pages是正确的,B方法取出来的确不对,pages始终等于1,total始终等于pageSize。很奇怪!仔细对照了两个方法之后找到了原因。方法A:这是se…

    2025年6月20日
    7
  • 三维坐标系旋转——旋转矩阵到旋转角之间的换算

    三维坐标系旋转——旋转矩阵到旋转角之间的换算相关文章 matlab 相机标定获取内参旋转矩阵到旋转角之间的换算 solvepnp 单目三维位姿估计利用二维码求解相机世界坐标 solvepnp 单目三维位姿估计理论在做单目三维位姿估计 即估计目标物相对相机的姿态或相机相对目标物的姿态 时会用到 solvepnp 函数 函数原型为 cv2 solvePnP objectPoints i

    2025年10月11日
    5

发表回复

您的邮箱地址不会被公开。 必填项已用 * 标注

关注全栈程序员社区公众号