Conditional Generative Adversarial Network

Conditional Generative Adversarial Networks (cGANs) are a type of generative model designed to create new data samples conditioned on specific input information, aiming to generate realistic and diverse outputs matching given constraints. Current research focuses on applying cGANs to diverse fields, leveraging architectures like Pix2Pix and CycleGAN, and exploring variations such as those incorporating diffusion models or transformer networks for improved performance and stability. This approach holds significant promise for various applications, including medical imaging (e.g., synthesizing missing data or enhancing image quality), manufacturing (generating manufacturable designs), and other domains requiring data augmentation or realistic data synthesis where obtaining real data is difficult or expensive. The ability to generate high-quality synthetic data addresses limitations in data availability and privacy concerns, ultimately improving the performance and generalizability of downstream machine learning models.

Papers

April 25, 2024

DE-CGAN: Boosting rTMS Treatment Prediction with Diversity Enhancing Conditional Generative Adversarial Networks
Matthew Squires, Xiaohui Tao, Soman Elangovan, Raj Gururajan, Haoran Xie, Xujuan Zhou, Yuefeng Li, U Rajendra Acharya
Conditional Generative Adversarial Network Generative Diversity Transcranial Magnetic Stimulation Functional Network Connectivity

April 21, 2024

Generalized Regression with Conditional GANs
Deddy Jobson, Eddy Hudson
Novel Regression Conditional Generative Adversarial Network Linear Regression Long Tailed Data Regression Problem Conditional GAN Prediction Function

April 19, 2024

PATE-TripleGAN: Privacy-Preserving Image Synthesis with Gaussian Differential Privacy
Zepeng Jiang, Weiwei Ni, Yifan Zhang
Differential Privacy Image Synthesis Privacy Preserving Conditional Generative Adversarial Network

April 15, 2024

Watermark-embedded Adversarial Examples for Copyright Protection against Diffusion Models
Peifei Zhu, Tsubasa Takahashi, Hirokatsu Kataoka
Diffusion Model Adversarial Example Conditional Generative Adversarial Network Adversarial Loss Copyright Protection Visible Watermark

March 31, 2024

GAN with Skip Patch Discriminator for Biological Electron Microscopy Image Generation
Nishith Ranjon Roy, Nailah Rawnaq, Tulin Kaman
Generative Adversarial Network Image to Image Translation Conditional Generative Adversarial Network Electron Microscopy

March 10, 2024

On depth prediction for autonomous driving using self-supervised learning
Houssem Boulahbal
Autonomous Driving Self Supervised Learning Conditional Generative Adversarial Network Depth Prediction Self Supervised Depth Conditional GANs

March 5, 2024

(Un)paired signal-to-signal translation with 1D conditional GANs
Eric Easthope
Image to Image Translation Conditional Generative Adversarial Network CycleGAN Model Conditional GANs Signal to Signal Translation

February 29, 2024

Learning to Find Missing Video Frames with Synthetic Data Augmentation: A General Framework and Application in Generating Thermal Images Using RGB Cameras
Mathias Viborg Andersen, Ross Greer, Andreas Møgelmose, Mohan Trivedi
Generative Model Conditional Generative Adversarial Network General Framework Thermal Image Vehicle Perception Synthetic Data Augmentation RGB Camera

February 22, 2024

Deep Generative Model-based Synthesis of Four-bar Linkage Mechanisms with Target Conditions
Sumin Lee, Jihoon Kim, Namwoo Kang
Conditional Generative Adversarial Network Linkage Model Bar Mechanism Target Identification Mechanism Synthesis Learning Based Generative

February 2, 2024

Ambient-Pix2PixGAN for Translating Medical Images from Noisy Data
Wentao Chen, Xichen Xu, Jie Luo, Weimin Zhou
Medical Image Conditional Generative Adversarial Network Noisy Data GAN Architecture Ambient Sound Based Augmentation Medical Image Translation

February 1, 2024

mmID: High-Resolution mmWave Imaging for Human Identification
Sakila S. Jayaweera, Sai Deepika Regani, Yuqian Hu, Beibei Wang, K. J. Ray Liu
Conditional Generative Adversarial Network Millimeter Wave Human Identification

January 22, 2024

Simulating Nighttime Visible Satellite Imagery of Tropical Cyclones Using Conditional Generative Adversarial Networks
Jinghuai Yao, Puyuan Du, Yucheng Zhao, Yubo Wang
Conditional Generative Adversarial Network Tropical Cyclone Nighttime Datasets Solar Radiation

December 30, 2023

Machine Learning (ML)-assisted Beam Management in millimeter (mm)Wave Distributed Multiple Input Multiple Output (D-MIMO) systems
Karthik R M, Dhiraj Nagaraja Hegde, Muris Sarajlic, Abhishek Sarkar
Machine Learning C Gan Conditional Generative Adversarial Network Multiple Input Multiple Output mmWave Signal Beam Prediction Wireless Node Beam Management

December 20, 2023

December 8, 2023

Synthesizing Traffic Datasets using Graph Neural Networks
Daniel Rodriguez-Criado, Maria Chli, Luis J. Manso, George Vogiatzis
Graph Neural Network Conditional Generative Adversarial Network Traffic Scenario Traffic Simulation Traffic Datasets

November 18, 2023

Diverse Shape Completion via Style Modulated Generative Adversarial Networks
Wesley Khademi, Li Fuxin
Ground Truth Conditional Generative Adversarial Network Shape Completion Model Completion Complete Shape Style Based Generative Adversarial Network

October 16, 2023

Style transfer between Microscopy and Magnetic Resonance Imaging via Generative Adversarial Network in small sample size settings
Monika Pytlarz, Adrian Onicas, Alessandro Crimi
Generative Adversarial Network Style Transfer Magnetic Resonance Imaging Conditional Generative Adversarial Network Histopathology Image Volumetric Representation Small Sample

October 12, 2023

A Benchmarking Protocol for SAR Colorization: From Regression to Deep Learning Approaches
Kangqing Shen, Gemine Vivone, Xiaoyuan Yang, Simone Lolli, Michael Schmitt
Deep Learning Novel Regression Synthetic Aperture Radar Conditional Generative Adversarial Network Benchmark Framework

September 27, 2023

P2I-NET: Mapping Camera Pose to Image via Adversarial Learning for New View Synthesis in Real Indoor Environments
Xujie Kang, Kanglin Liu, Jiang Duan, Yuanhao Gong, Guoping Qiu
Novel View Synthesis Adversarial Learning Conditional Generative Adversarial Network Indoor Scene Camera Pose View Generation

Conditional Generative Adversarial Network

Papers

DE-CGAN: Boosting rTMS Treatment Prediction with Diversity Enhancing Conditional Generative Adversarial Networks

Generalized Regression with Conditional GANs

PATE-TripleGAN: Privacy-Preserving Image Synthesis with Gaussian Differential Privacy

Watermark-embedded Adversarial Examples for Copyright Protection against Diffusion Models

GAN with Skip Patch Discriminator for Biological Electron Microscopy Image Generation

On depth prediction for autonomous driving using self-supervised learning

(Un)paired signal-to-signal translation with 1D conditional GANs

Learning to Find Missing Video Frames with Synthetic Data Augmentation: A General Framework and Application in Generating Thermal Images Using RGB Cameras

Deep Generative Model-based Synthesis of Four-bar Linkage Mechanisms with Target Conditions

Ambient-Pix2PixGAN for Translating Medical Images from Noisy Data

mmID: High-Resolution mmWave Imaging for Human Identification

Simulating Nighttime Visible Satellite Imagery of Tropical Cyclones Using Conditional Generative Adversarial Networks

Machine Learning (ML)-assisted Beam Management in millimeter (mm)Wave Distributed Multiple Input Multiple Output (D-MIMO) systems

Pixel-to-Abundance Translation: Conditional Generative Adversarial Networks Based on Patch Transformer for Hyperspectral Unmixing

A self-attention-based differentially private tabular GAN with high data utility

Synthesizing Traffic Datasets using Graph Neural Networks

Diverse Shape Completion via Style Modulated Generative Adversarial Networks

Style transfer between Microscopy and Magnetic Resonance Imaging via Generative Adversarial Network in small sample size settings

A Benchmarking Protocol for SAR Colorization: From Regression to Deep Learning Approaches

P2I-NET: Mapping Camera Pose to Image via Adversarial Learning for New View Synthesis in Real Indoor Environments