专栏首页机器学习与生成对抗网络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)

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

Sparse 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

5291

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

本文分享自微信公众号 - 机器学习与生成对抗网络(AI_bryant8),作者:bryant8

原文出处及转载信息见文内详细说明,如有侵权,请联系 yunjia_community@tencent.com 删除。

原始发表时间:2020-07-25

本文参与腾讯云自媒体分享计划,欢迎正在阅读的你也加入,一起分享。

我来说两句

0 条评论
登录 后参与评论

相关文章

  • 用Python实现科研自动化

    这个学期如期开课了,虽然是在家里。这学期我导开了一门《高等教育管理专题研究》,一口气给了11个专题。为了对这11个专题的文献分布情况有一个粗略的印象,我觉得都得...

    公众号机器学习与生成对抗网络
  • 中文论文 |《基于深度神经网络的少样本学习综述》

    最近深度神经网络已经在监督识别任务上取得了令人振奋的突破,但是深度神经网络要求每个类都有足够多的且完全标注的训练数据。如何从少数训练样本中学习并识别新的类别,对...

    公众号机器学习与生成对抗网络
  • C++引用和指针以及const常量限定符,能说一二吗?

    最近后台有收到问,能不能分享更多一些方面的干货呢、比如深度学习其他方面、简单易懂的知识,甚至一些琐碎杂乱的计算机基础知识点?

    公众号机器学习与生成对抗网络
  • JS 单例模式

    单例模式 (Singleton) 的实现在于保证一个特定类只有一个实例,第二次使用同一个类创建新对象的时候,应该得到与第一次创建对象完全相同的对象。 当创建一个...

    前端下午茶
  • Spring容器和Bean加载

    IOC(控制反转):对于组件的控制权进行了转移,传统的程序设计是由客户端new出对象,是程序主动创建所依赖的对象。而IOC是专门将对象的创建交给容器处理,组件的...

    春哥大魔王
  • java的IO模型

    本文主要是重新梳理了Java的IO模型,基于之前NIO的文章进行补充,为学习Netty做准备。

    贪挽懒月
  • CoordinatorLayout的使用如此简单

    曾在网上找了一些关于CoordinatorLayout的教程,大部分文章都是把CoordinatorLayout、AppbarLayout、Collapsing...

    非著名程序员
  • 4-8 打包分析

    上一节4-3~8 code-splitting,懒加载,预拉取,预加载 讲到如何对代码进行 code splitting。那么如何判断我们的代码要进行code...

    love丁酥酥
  • 干货!机器人、无人机产业链全景图

    来源:新材料在线

    机器人网
  • 美食与人工智能,每天不知道吃什么?用人工智能为你生成食谱

    本文是作者ML95-GONG,参加了 「 30天AI训练营 」首期所写的学习总结。作者是MixLab社区成员,同时是MixLab共建者,具有工业设计/交互设计/...

    mixlab

扫码关注云+社区

领取腾讯云代金券