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Methods/SAGAN

SAGAN

Self-Attention GAN

Computer VisionIntroduced 2000138 papers
Source Paper

Description

The Self-Attention Generative Adversarial Network, or SAGAN, allows for attention-driven, long-range dependency modeling for image generation tasks. Traditional convolutional GANs generate high-resolution details as a function of only spatially local points in lower-resolution feature maps. In SAGAN, details can be generated using cues from all feature locations. Moreover, the discriminator can check that highly detailed features in distant portions of the image are consistent with each other.

Papers Using This Method

ParaGAN: A Scalable Distributed Training Framework for Generative Adversarial Networks2024-11-06Unsupervised Panoptic Interpretation of Latent Spaces in GANs Using Space-Filling Vector Quantization2024-10-27Spatial-aware Attention Generative Adversarial Network for Semi-supervised Anomaly Detection in Medical Image2024-05-21On quantifying and improving realism of images generated with diffusion2023-09-26Precision-Recall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows2023-09-21A Strategic Framework for Optimal Decisions in Football 1-vs-1 Shot-Taking Situations: An Integrated Approach of Machine Learning, Theory-Based Modeling, and Game Theory2023-07-27Pyrus Base: An Open Source Python Framework for the RoboCup 2D Soccer Simulation2023-07-22Diffusion Models Beat GANs on Image Classification2023-07-17Diversity is Strength: Mastering Football Full Game with Interactive Reinforcement Learning of Multiple AIs2023-06-28Rosetta Neurons: Mining the Common Units in a Model Zoo2023-06-15Toward more accurate and generalizable brain deformation estimators for traumatic brain injury detection with unsupervised domain adaptation2023-06-08FOOCTTS: Generating Arabic Speech with Acoustic Environment for Football Commentator2023-06-07Action valuation of on- and off-ball soccer players based on multi-agent deep reinforcement learning2023-05-29Is Centralized Training with Decentralized Execution Framework Centralized Enough for MARL?2023-05-27Adaptive action supervision in reinforcement learning from real-world multi-agent demonstrations2023-05-22An Empirical Study on Google Research Football Multi-agent Scenarios2023-05-16The MuSe 2023 Multimodal Sentiment Analysis Challenge: Mimicked Emotions, Cross-Cultural Humour, and Personalisation2023-05-05SportsMOT: A Large Multi-Object Tracking Dataset in Multiple Sports Scenes2023-04-11VARS: Video Assistant Referee System for Automated Soccer Decision Making from Multiple Views2023-04-10Towards Active Learning for Action Spotting in Association Football Videos2023-04-09