adversarial training

Reinforcement Learning Based Text Style Transfer without Parallel Training Corpus NAACL 2019 RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimation CVPR 2019 Retrieval-Enhanced Adversarial Training for Neural Response Generation ACL 2019 Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness NeurIPS 2019 Revisiting LSTM Networks for Semi-Supervised Text Classification via Mixed Objective Function AAAI 2019 Rob-GAN: Generator, Discriminator, and Adversarial Attacker CVPR 2019 Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient AAAI 2019 Robustness via Curvature Regularization, and Vice Versa CVPR 2019 Scene-level Pose Estimation for Multiple Instances of Densely Packed Objects CoRL 2019 Self-Supervised Dialogue Learning ACL 2019 Semantically Tied Paired Cycle Consistency for Zero-Shot Sketch-Based Image Retrieval CVPR 2019 Semi-Supervised Learning by Augmented Distribution Alignment ICCV 2019 Soft Representation Learning for Sparse Transfer ACL 2019 SparseFool: A Few Pixels Make a Big Difference CVPR 2019 Spatial Correspondence With Generative Adversarial Network: Learning Depth From Monocular Videos ICCV 2019 Spatiotemporal CNN for Video Object Segmentation CVPR 2019 Speaker Adversarial Training of DPGMM-Based Feature Extractor for Zero-Resource Languages Interspeech 2019 State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations ICML 2019 Structured Knowledge Distillation for Semantic Segmentation CVPR 2019 Structure-Preserving Stereoscopic View Synthesis With Multi-Scale Adversarial Correlation Matching CVPR 2019 Text Processing Like Humans Do: Visually Attacking and Shielding NLP Systems NAACL 2019 The Limitations of Adversarial Training and the Blind-Spot Attack ICLR 2019 Through-Wall Human Mesh Recovery Using Radio Signals ICCV 2019 Topics to Avoid: Demoting Latent Confounds in Text Classification EMNLP 2019 Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective IJCAI 2019