generative adversarial network

Multi-Class Multi-Instance Count Conditioned Adversarial Image Generation ICCV 2021 Multidimensional Uncertainty-Aware Evidential Neural Networks AAAI 2021 Multi-Frame Recurrent Adversarial Network for Moving Object Segmentation WACV 2021 Multi-level Generative Models for Partial Label Learning with Non-random Label Noise IJCAI 2021 Multimodal Trajectory Predictions for Autonomous Driving Without a Detailed Prior Map WACV 2021 Multi-SpectroGAN: High-Diversity and High-Fidelity Spectrogram Generation with Adversarial Style Combination for Speech Synthesis AAAI 2021 MUST-GAN: Multi-Level Statistics Transfer for Self-Driven Person Image Generation CVPR 2021 Naturalistic Physical Adversarial Patch for Object Detectors ICCV 2021 Navigating the GAN Parameter Space for Semantic Image Editing CVPR 2021 Negative Data Augmentation ICLR 2021 Non-asymptotic Error Bounds for Bidirectional GANs NeurIPS 2021 Normalized Avatar Synthesis Using StyleGAN and Perceptual Refinement CVPR 2021 Not Just Compete, but Collaborate: Local Image-to-Image Translation via Cooperative Mask Prediction CVPR 2021 Object-Centric Image Generation from Layouts AAAI 2021 Object Segmentation Without Labels with Large-Scale Generative Models ICML 2021 On Characterizing GAN Convergence Through Proximal Duality Gap ICML 2021 One-shot Face Reenactment Using Appearance Adaptive Normalization AAAI 2021 Online Multi-Granularity Distillation for GAN Compression ICCV 2021 On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction and An Optimal Training Framework ICML 2021 On Self-Supervised Image Representations for GAN Evaluation ICLR 2021 On the Frequency Bias of Generative Models NeurIPS 2021 On the Privacy Properties of GAN-generated Samples AISTATS 2021 OpenGAN: Open-Set Recognition via Open Data Generation ICCV 2021 Open-Set Audio Classification with Limited Training Resources Based on Augmentation Enhanced Variational Auto-Encoder GAN with Detection-Classification Joint Training Interspeech 2021 ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-Supervised Continual Learning CVPR 2021