Synthetic Data Augmentation

Follow this topic Ask about this topic

Momentum

24 papers in the last four weeks, up 85% on the four weeks before. 0.2% of all new papers.

Jul 13Week of Sep 28

Latest papers 294

All topics

Where Detectors Fail: Probing Generative Space for Generalizable AI-Generated Image Detection
May 24, 2026Zijie Cao, Weijie Tu, Yao Xiao +3Synthetic Data Augmentation AI-Generated Image Detection
School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China · Australian National University, Canberra, Australia · Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China +1
Bilevel Optimization of Synthetic Trajectories for Multi-Turn LLM Fine-Tuning
May 23, 2026Shresth Verma, Mauricio Tec, Cheol Woo Kim +2Synthetic Data Augmentation Offline RL
Harvard University Cambridge, MA · Georgia Institute of Technology Atlanta, GA
When Does Synthetic Patent Data Help? Volume-Fidelity Trade-offs in Low-Resource Multi-Label Classification
May 22, 2026Amirhossein Yousefiramandi, Ciaran CooneySynthetic Data Augmentation Multi-Label Classification
Clarivate, Intellectual Property · Barcelona, Spain 08025
Generator-Refiner-Examiner: A Tri-Module Data Augmentation Framework for 3D Human Avatar Learning from Monocular Videos
May 22, 2026Gangjian Zhang, Jian Shu, Sicheng Yu +3Synthetic Data Augmentation 3D Reconstruction
HKUST(GZ) Guangzhou, China · Nanyang Technological University Singapore
Class-Dependent Hybrid Data Augmentation for Multiclass Migraine Classification under Severe Class Imbalance
May 22, 2026Elvin Somón, Miguel A. Gutiérrez-NaranjoClass-Imbalanced Learning Synthetic Data Augmentation
Department of Computer Science and Artificial Intelligence University of Seville, Seville, Spain
SSDAU: Structured Semantic Data Augmentation for Joint Entity and Relation Extraction
May 22, 2026Jiawei He, Mengyu Shi, Jiawei Liu +6Relation Extraction Synthetic Data Augmentation
State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China · Amap, Alibaba Group, China · University of Alberta, Edmonton, Canada +1
RS2AD-LiDAR: End-to-End Autonomous Driving LiDAR Data Generation from Roadside Sensor Observations
May 22, 2026Runyi Huang, Ni Ding, Ruidan Xing +3Synthetic Data Augmentation Autonomous Driving Perception
State Key Laboratory of Intelligent Green Vehicle and Mobility, Tsinghua University, Beijing, 100084, China. · School of Vehicle and Mobility, Tsinghua University, Beijing, 100084, China. · College of Artificial Intelligence, Tsinghua University, Beijing, 100083, China. +2
Do Synthetic Brain MRIs Reliably Improve Tumour Classification? A StyleGAN2-ADA Class-Plane Augmentation Study on BRISC 2025
May 21, 2026José Rafael Noriega CedeñoSynthetic Data Augmentation Medical Image Classification
Faculty of Applied Sciences and Technology
Making the Discrete Continuous: Synthetic RAW Augmentations for Fine-Grained Evaluation of Person Detection Performance in Low Light
May 21, 2026Valeria Pais, Malena Mendilaharzu, Daniele Faccio +3Synthetic Data Augmentation Autonomous Driving Perception
University of Glasgow · Chapel Ln, Glasgow G11 6EW, UK · Dotphoton +2
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training
May 20, 2026Hongzhi Ruan, Pei Liu, Weiliang Ma +5Autonomous Driving Datasets Synthetic Data Augmentation
Li Auto · HKUST (GZ) · HKUST
Q-SYNTH: Hybrid Quantum-Classical Adversarial Augmentation for Imbalanced Fraud Detection
May 20, 2026Adam Innan, Mansour El Alami, Nouhaila Innan +2Class-Imbalanced Learning Synthetic Data Augmentation
Quantum Physics and Spintronics Team, LPMC, Faculty of Sciences Ben M’sick, Hassan II University of Casablanca, Morocco · eBRAIN Lab, Division of Engineering, New York University Abu Dhabi (NYUAD), Abu Dhabi, UAE · Center for Quantum and Topological Systems (CQTS), NYUAD Research Institute, NYUAD, Abu Dhabi, UAE
TextSculptor: Training and Benchmarking Scene Text Editing
May 20, 2026Yiheng Lin, Siyu Jiao, Xiaohan Lan +12Synthetic Data Augmentation Text-Guided Image Editing
Beijing Jiaotong University · Bytedance
CAD-Free Learning of Spacecraft Pose Estimators via NeRF-Based Augmentations
May 19, 2026Antoine Legrand, Renaud Detry, Christophe De VleeschouwerSynthetic-to-Real Domain Adaptation Synthetic Data Augmentation
Department of Electrical Engineering (ELEN), ICTEAM, UCLouvain · Department of Electrical Engineering (ESAT), KU Leuven · Aerospacelab +1
What Makes Synthetic Data Effective in Image Segmentation
May 19, 2026Jinjin Zhang, Xiefan Guo, Yizhou Jin +2Synthetic Data Augmentation Image Segmentation
State Key Laboratory of Complex and Critical Software Environment, Beihang University, Beijing 100191, China · School of Computer Science and Engineering, Beihang University, Beijing 100191, China
The MixCount Dataset: Bridging the Data Gap for Open-Vocabulary Object Counting
May 18, 2026Corentin Dumery, Niki Amini-Naieni, Shervin Naini +1Synthetic Data Augmentation Object Counting
EPFL · University of Oxford · Northwestern University
Systematic Evaluation of the Quality of Synthetic Clinical Notes Rephrased by LLMs at Million-Note Scale
May 18, 2026Jinghui Liu, Sarvesh Soni, Anthony NguyenSynthetic Data Augmentation Automated Medical Coding
Australian e-Health Research Centre, CSIRO, Australia · National Library of Medicine, National Institutes of Health, USA
Can Large Language Models Imitate Human Speech for Clinical Assessment? LLM-Driven Data Augmentation for Cognitive Score Prediction
May 15, 2026Si-Belkacem Yamine Ketir, Lenard Paulo Tamayo, Shohei Hisada +3Class-Imbalanced Learning Synthetic Data Augmentation
Télécom SudParis, France · Nara Institute of Science and Technology, Japan
Flow Matching with Optimized Subclass Priors for Medical Image Augmentation
May 15, 2026Felix Nützel, Mischa Dombrowski, Bernhard KainzFlow Matching Synthetic Data Augmentation
Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91052 Erlangen, Germany · Department of Computing, Imperial College London, London SW7 2AZ, UK
Bidirectional Fusion Guided by Cardiac Patterns for Semi-Supervised ECG Segmentation
May 15, 2026Jeonghwa Lim, Minje Park, Sunghoon JooSynthetic Data Augmentation Electrocardiography
VUNO Inc., Seoul, South Korea
DriveCtrl: Conditioned Sim-to-Real Driving Video Generation
May 14, 2026Haonan Zhao, Yiting Wang, Jingkun Chen +3Autonomous Driving Datasets Synthetic Data Augmentation
University of Warwick · 2Northwestern Polytechnical University · 3Queen Mary University of London
Reduce the Artifacts Bias for More Generalizable AI-Generated Image Detection
May 14, 2026Yiheng Li, Yang Yang, Zichang Tan +3Synthetic Data Augmentation Mixture of Experts
School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China · MAIS, Institute of Automation, Chinese Academy of Sciences, Beijing, China · Sangfor Technologies Inc. +4
Mitigating Data Scarcity in Psychological Defense Classification with Context-Aware Synthetic Augmentation
May 14, 2026Hoang-Thuy-Duong Vu, Quoc-Cuong Pham, Huy-Hieu PhamSynthetic Data Augmentation Text Classification
College of Engineering and Computer Science, VinUniversity, Hanoi, Vietnam · VinUni-Illinois Smart Health Center, VinUniversity, Hanoi, Vietnam · Center for Innovations in Health Sciences, VinUniversity, Hanoi, Vietnam
HIR-ALIGN: Enhancing Hyperspectral Image Restoration via Diffusion-Based Data Generation
May 13, 2026Li Pang, Heng Zhao, Yijia Zhang +2Synthetic Data Augmentation Unsupervised Domain Adaptation
Mitigating Illumination-Induced Domain Shift in Night-Time Pedestrian Detection for Intelligent Vehicles using Annotation-Preserving Diffusion Augmentation
May 13, 2026Franky George, Muhammad Khalid, Adil Khan +1Synthetic Data Augmentation Domain Adaptation
School of Digital and Physical Sciences, University of Hull, UK
Enhancing Domain Generalization in 3D Human Pose Estimation through Controllable Generative Augmentation
May 12, 2026Xinhao Hu, Yiyi Zhang, Liqing Zhang +1Synthetic Data Augmentation Domain Generalization
School of Computer Science, Shanghai Jiao Tong University
Few-Shot Synthetic Data Generation with Diffusion Models for Downstream Vision Tasks
May 12, 2026Daniil Dushenev, Nazariy Karpov, Daniil Zinovjev +2Class-Imbalanced Learning Synthetic Data Augmentation
National University of Science and Technology MISIS, Moscow, Russia
OverNaN: NaN-Aware Oversampling for Imbalanced Learning with Meaningful Missingness
May 12, 2026Amanda S BarnardClass-Imbalanced Learning Synthetic Data Augmentation
School of Computing Australian National University Acton, ACT 2601
More Than Meets the Eye: A Semantics-Aware Traffic Augmentation Framework for Generalizable Website Fingerprinting
May 12, 2026Youquan Xian, Xueying Zeng, Lingjia Meng +6Synthetic Data Augmentation Cross-Domain Generalization
School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, China · School of Computer Science and Engineering, Beihang University, Beijing, China · Zhongguancun Laboratory, Beijing, China +2
LiBaGS: Lightweight Boundary Gap Synthesis for Targeted Synthetic Data Selection
May 11, 2026Abhishek Moturu, Anna Goldenberg, Babak TaatiSynthetic Data Augmentation Training Data Selection
Department of Computer Science University of Toronto The Hospital for Sick Children UHN KITE Research Institute T-CAIREM Vector Institute · Department of Computer Science Department of Laboratory Medicine and Pathobiology University of Toronto The Hospital for Sick Children T-CAIREM Vector Institute · Department of Computer Science Institute of Biomedical Engineering University of Toronto Rehabilitation Sciences Institute UHN KITE Research Institute Vector Institute
Confidence-Guided Diffusion Augmentation for Enhanced Bangla Compound Character Recognition
May 11, 2026Md. Sultan Al RayhanSynthetic Data Augmentation Optical Character Recognition
Department of Computer Science and Engineering East West University, Dhaka, Bangladesh

May 24, 2026, cs.CVJ/K move · Enter open · S save

Where Detectors Fail: Probing Generative Space for Generalizable AI-Generated Image Detection

Zijie Cao, Weijie Tu, Yao Xiao, Weijian Deng+2

School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China · Australian National University, Canberra, Australia · Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China+1

Synthetic Data Augmentation AI-Generated Image Detection

Open paper AskPDF arXiv

Detecting AI-generated images (AIGI) remains challenging because detectors often fail to generalize to unseen generators. Although existing methods are trained on large datasets, their performance still degrades when generation settings change, indicating that data scale alone is insufficient and that limited coverage of generative variations during training is a key factor. Studies on generative model editing show that small changes in internal representations can produce diverse and meaningful image variations, many of which are not explored under standard sampling. Leveraging this insight, we propose PROBE (Probing Robustness via Boundary Exploration), a framework that improves detector generalization by actively exploring challenging regions of the generative process. Instead of treating the generator as a fixed data source, PROBE uses the detector as a critic to steer the generator through manifold-level modifications, producing realistic samples that are difficult to classify. These samples expose failure cases that are uncommon under standard data sampling strategies and are used to refine the detector. Experimental results across multiple benchmarks indicate that PROBE enhances generalization to unseen generators, resulting in more generalizable AIGI detection performance. Code and models are available at https://github.com/Amamiya-C/PROBE-AIGI-Detection

Momentum

Related topics

Latest papers 294