Data Augmentation

ICLR 2024arXiv:2310.10402

#2

Real-Fake: Effective Training Data Synthesis Through Distribution Matching

Jianhao Yuan, Jie Zhang, Shuyang Sun et al.

45

ICLR 2024arXiv:2403.12448

#3

Do Generated Data Always Help Contrastive Learning?

Yifei Wang, Jizhe Zhang, Yisen Wang

35

ECCV 2024arXiv:2406.08249

#4

Dataset Enhancement with Instance-Level Augmentations

Orest Kupyn, Christian Rupprecht

17

CVPR 2024arXiv:2403.10519

#5

Frozen Feature Augmentation for Few-Shot Image Classification

Andreas Bär, Neil Houlsby, Mostafa Dehghani et al.

16

AAAI 2024arXiv:2308.15068

#6

A Comprehensive Augmentation Framework for Anomaly Detection

Lin Jiang, Yaping Yan

anomaly detectiondata augmentationreconstruction-based approachsimulated anomalies+4

16

ECCV 2024arXiv:2408.00350

#7

Kill Two Birds with One Stone: Rethinking Data Augmentation for Deep Long-tailed Learning

Binwu Wang, Pengkun Wang, Wei Xu et al.

A Simple Background Augmentation Method for Object Detection with Diffusion Model

YUHANG LI, Xin Dong, Chen Chen et al.

object detectioninstance segmentationdata augmentationdiffusion models+4

15

ECCV 2024arXiv:2310.09739

#9

AugUndo: Scaling Up Augmentations for Monocular Depth Completion and Estimation

Yangchao Wu, Tian Yu Liu, Hyoungseob Park et al.

monocular depth completionunsupervised depth estimationgeometric augmentationsdepth map warping+3

15

ECCV 2024arXiv:2407.02286

#10

Rethinking Data Augmentation for Robust LiDAR Semantic Segmentation in Adverse Weather

Junsung Park, Kyungmin Kim, Hyunjung Shim

lidar semantic segmentationadverse weather robustnessgeometric perturbationpoint drop phenomenon+4

13

ICCV 2025arXiv:2508.06492

#11

Effective Training Data Synthesis for Improving MLLM Chart Understanding

Yuwei Yang, Zeyu Zhang, Yunzhong Hou et al.

chart understandingmultimodal large language modelsdata synthesis pipelinesynthetic chart generation+3

10

ECCV 2024arXiv:2409.07307

#12

11293 Cross-Class Feature Augmentation for Class Incremental Learning

Taehoon Kim, JaeYoo Park, Bohyung Han

MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL

Claas Voelcker, Marcel Hussing, ERIC EATON et al.

Data Augmentation via Latent Diffusion for Saliency Prediction

Bahar Aydemir, Deblina Bhattacharjee, Tong Zhang et al.

7

AAAI 2025arXiv:2405.19610

#15

Factor Augmented Tensor-on-Tensor Neural Networks

Guanhao Zhou, Yuefeng Han, Xiufan Yu

7

CVPR 2024arXiv:2412.13081

#16

Prompt Augmentation for Self-supervised Text-guided Image Manipulation

Rumeysa Bodur, Binod Bhattarai, Tae-Kyun Kim

6

AAAI 2025arXiv:2412.11807

#17

PhysAug: A Physical-guided and Frequency-based Data Augmentation for Single-Domain Generalized Object Detection

Xiaoran Xu, Jiangang Yang, Wenhui Shi et al.

6

AAAI 2025arXiv:2412.10029

#18

Enhancing Fine-Grained Vision-Language Pretraining with Negative Augmented Samples

Yeyuan Wang, Dehong Gao, Lei Yi et al.

4

AAAI 2024arXiv:2312.07951

#19

Semantic-Aware Data Augmentation for Text-to-Image Synthesis

Zhaorui Tan, Xi Yang, Kaizhu Huang

text-to-image synthesissemantic data augmentationattention mechanismcontrastive learning+4

4

AAAI 2025arXiv:2312.03289

#20

Enhancing Robustness in Incremental Learning with Adversarial Training

Seungju Cho, Hongsin Lee, Changick Kim

4

CVPR 2025arXiv:2503.13385

#21

GenDataAgent: On-the-fly Dataset Augmentation with Synthetic Data

Zhiteng Li, Lele Chen, Jerone Andrews et al.

Scale Efficient Training for Large Datasets

Qing Zhou, Junyu Gao, Qi Wang

3

ECCV 2024arXiv:2409.04820

#23

FreeAugment: Data Augmentation Search Across All Degrees of Freedom

Tom Bekor, Niv Nayman, Lihi Zelnik-Manor

data augmentation searchautomatic image transformationsdifferentiable optimizationtransformation magnitude learning+2

2

AAAI 2025arXiv:2405.14115

#24

Representation Space Augmentation for Effective Self-Supervised Learning on Tabular Data

Moonjung Eo, Kyungeun Lee, Hye-Seung Cho et al.

Configuring Data Augmentations to Reduce Variance Shift in Positional Embedding of Vision Transformers

Bum Jun Kim, Sang Woo Kim

2

AAAI 2025arXiv:2412.16050

#26

Label-Efficient Data Augmentation with Video Diffusion Models for Guidewire Segmentation in Cardiac Fluoroscopy

Shaoyan Pan, Yikang Liu, Lin Zhao et al.

1

AAAI 2025arXiv:2412.11410

#27

MGDA: Model-based Goal Data Augmentation for Offline Goal-conditioned Weighted Supervised Learning

Xing Lei, Xuetao Zhang, Donglin Wang

1

ICML 2025arXiv:2505.22196

#28

An Augmentation-Aware Theory for Self-Supervised Contrastive Learning

Jingyi Cui, Hongwei Wen, Yisen Wang

1

CVPR 2024arXiv:2401.04727

#29

Revisiting Adversarial Training at Scale

Zeyu Wang, Xianhang li, Hongru Zhu et al.

ICLR 2024arXiv:2310.17786

#30

Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates

Nicholas Corrado, Josiah Hanna

#31

Parametric Augmentation for Time Series Contrastive Learning

Xu Zheng, Tianchun Wang, Wei Cheng et al.

Domain-wise Data Acquisition to Improve Performance under Distribution Shift

Yue He, Dongbai Li, Pengfei Tian et al.

domain adaptationdistribution shiftdata acquisitioncross-distribution generalization+3

ICLR 2024arXiv:2402.12181

#33

Revisiting Data Augmentation in Deep Reinforcement Learning

Jianshu Hu, Yunpeng Jiang, Paul Weng

ICML 2025arXiv:2504.05250

#34

When Dynamic Data Selection Meets Data Augmentation: Achieving Enhanced Training Acceleration

Suorong Yang, Peng Ye, Furao Shen et al.

PEAKS: Selecting Key Training Examples Incrementally via Prediction Error Anchored by Kernel Similarity

Mustafa Burak Gurbuz, Xingyu Zheng, Constantine Dovrolis

#36

The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective

Chi-Heng Lin, Chiraag Kaushik, Eva Dyer et al.

data augmentationspectral regularizationcovariance matrix eigenvaluesoverparameterized linear models+4

CVPR 2024arXiv:2402.05937

#37

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation

Piyush Lalitkumar Tiwary, Kinjawl Bhattacharyya, Prathosh AP

InstaGen: Enhancing Object Detection by Training on Synthetic Dataset

Chengjian Feng, Yujie Zhong, Zequn Jie et al.

#39

Causal Action Influence Aware Counterfactual Data Augmentation

Núria Armengol Urpí, Marco Bagatella, Marin Vlastelica et al.

causal influence quantificationcounterfactual data augmentationoffline reinforcement learningrobustness to distributional shift+3

ICLR 2024arXiv:2302.07944

#40

Effective Data Augmentation With Diffusion Models

Brandon Trabucco, Kyle Doherty, Max Gurinas et al.

ICLR 2024arXiv:2403.10834

#41

Rethinking Point Cloud Data Augmentation: Topologically Consistent Deformation

Jian Bi, Qianliang Wu, Xiang Li et al.

Curvature Enhanced Data Augmentation for Regression

Ilya Kaufman, Omri Azencot

On Trajectory Augmentations for Off-Policy Evaluation

Ge Gao, Qitong Gao, Xi Yang et al.

SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation

Uiwon Hwang, Jonghyun Lee, Juhyeon Shin et al.

CVPR 2024arXiv:2403.06606

#45

SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation

Mucong Ding, Bang An, Yuancheng Xu et al.

In Search of a Data Transformation That Accelerates Neural Field Training

Junwon Seo, Sangyoon Lee, Kwang In Kim et al.

Distributionally Generative Augmentation for Fair Facial Attribute Classification

Fengda Zhang, Qianpei He, Kun Kuang et al.

ICLR 2024arXiv:2310.12972

#48

CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning

Liyiming Ke, Yunchu Zhang, Abhay Deshpande et al.

CVPR 2024arXiv:2405.10185

#49

Domain Gap Embeddings for Generative Dataset Augmentation

Yinong Oliver Wang, Younjoon Chung, Chen Henry Wu et al.

Instruct Where the Model Fails: Generative Data Augmentation via Guided Self-contrastive Fine-tuning

Weijian Ma, Ruoxin Chen, Keyue Zhang et al.

Sparse Enhanced Network: An Adversarial Generation Method for Robust Augmentation in Sequential Recommendation

Junyang Chen, Guoxuan Zou, Pan Zhou et al.

DiverGen: Improving Instance Segmentation by Learning Wider Data Distribution with More Diverse Generative Data

Chengxiang Fan, Muzhi Zhu, Hao Chen et al.

AAAI 2025arXiv:2402.18292

#53

FSL-Rectifier: Rectify Outliers in Few-Shot Learning via Test-Time Augmentation

Yunwei Bai, Ying Kiat Tan, Shiming Chen et al.

AAAI 2025arXiv:2502.18249

#54

Data Augmentation for Instruction Following Policies via Trajectory Segmentation

Niklas Hoepner, Ilaria Tiddi, Herke van Hoof

For Better or For Worse? Learning Minimum Variance Features With Label Augmentation

Muthu Chidambaram, Rong Ge

Iterative Counterfactual Data Augmentation

Mitchell Plyler, Min Chi

AAAI 2024arXiv:2312.11276

#57

Compositional Generalization for Multi-Label Text Classification: A Data-Augmentation Approach

Yuyang Chai, Zhuang Li, Jiahui Liu et al.

multi-label text classificationcompositional generalizationdata augmentationtext generation models+2

dynamic graph neural networksgraph data augmentationtemporal consistencygraph rationalization+3

#58

ACAMDA: Improving Data Efficiency in Reinforcement Learning through Guided Counterfactual Data Augmentation

Yuewen Sun, Erli Wang, Biwei Huang et al.

Adversity-aware Few-shot Named Entity Recognition via Augmentation Learning

Li Huang, Haowen Liu, Qiang Gao et al.

GNN-Transformer Task Planning Enhanced with Semantic-Driven Data Augmentation

Soojin Jeong, Seongwan Byeon, Sangwoo Kim et al.

Rationalizing and Augmenting Dynamic Graph Neural Networks

Guibin Zhang, Yiyan Qi, Ziyang Cheng et al.

ICLR 2025

ECCV 2024arXiv:2312.04763

#62

Enhancing Recipe Retrieval with Foundation Models: A Data Augmentation Perspective

Fangzhou Song, Bin Zhu, Yanbin Hao et al.

cross-modal retrievalrecipe retrievaldata augmentationfoundation models+3

ICCV 2025arXiv:2507.04302

#63

Split-and-Combine: Enhancing Style Augmentation for Single Domain Generalization

Zhen Zhang, Zhen Zhang, Qianlong Dang et al.

Progressive Distribution Bridging: Unsupervised Adaptation for Large-scale Pre-trained Models via Adaptive Auxiliary Data

Weinan He, Yixin Zhang, Zilei Wang

ADD: Attribution-Driven Data Augmentation Framework for Boosting Image Super-Resolution

Zeyu Mi, Yu-Bin Yang

A Simple Data Augmentation for Feature Distribution Skewed Federated Learning

Yunlu Yan, Huazhu Fu, Yuexiang Li et al.

Adversarial Data Augmentation for Single Domain Generalization via Lyapunov Exponent-Guided Optimization

ZUYU ZHANG, Ning Chen, Yongshan Liu et al.

single domain generalizationdata augmentation techniquesdomain shift adaptationlyapunov exponent guidance+4

CVPR 2025arXiv:2503.00823

#68

Scaling and Taming Adversarial Training with Synthetic Data

Juntao Wu, Xianting Huang, Yu Chen et al.

APT: Adaptive Personalized Training for Diffusion Models with Limited Data

JungWoo Chae, Jiyoon Kim, Jaewoong Choi et al.

Task-Agnostic Guided Feature Expansion for Class-Incremental Learning

Bowen Zheng, Da-Wei Zhou, Han-Jia Ye et al.

CVPR 2025arXiv:2411.19946

#71

DELT: A Simple Diversity-driven EarlyLate Training for Dataset Distillation

Zhiqiang Shen, Ammar Sherif, Zeyuan Yin et al.

domain adaptationvision-language modelstext-guided augmentationunseen domains+2

#72

Generalizing to Unseen Domains via Text-guided Augmentation

Daiqing Qi, Handong Zhao, Aidong Zhang et al.

ECCV 2024

ECCV 2024arXiv:2409.06290

#73

EntAugment: Entropy-Driven Adaptive Data Augmentation Framework for Image Classification

Suorong Yang, Furao Shen, Jian Zhao

data augmentationimage classificationentropy regularizationadaptive augmentation+2

#74

Generative Hard Example Augmentation for Semantic Point Cloud Segmentation

Qi Zhang, Jibin Peng, Zhao Huang et al.

Improving the Transferability of Adversarial Attacks on Face Recognition with Diverse Parameters Augmentation

Fengfan Zhou, Bangjie Yin, Hefei Ling et al.

Test-time Augmentation Improves Efficiency in Conformal Prediction

Divya M Shanmugam, Helen Lu, Swami Sankaranarayanan et al.

Boosting Adversarial Transferability through Augmentation in Hypothesis Space

Yu Guo, Weiquan Liu, Qingshan Xu et al.

AugGen: Synthetic Augmentation using Diffusion Models Can Improve Recognition

Parsa Rahimi, Damien Teney, Sébastien Marcel

Prototype-based Contrastive Learning with Stage-wise Progressive Augmentation for Self-Supervised Fine-Grained Learning

BaoFeng Tan, Xiu-Shen Wei, Lin Zhao

Diffusion-Guided Graph Data Augmentation

Maria Marrium, Arif Mahmood, Muhammad Haris Khan et al.

Beyond Clean Training Data: A Versatile and Model-Agnostic Framework for Out-of-Distribution Detection with Contaminated Training Data

Yuchuan Li, Jae-Mo Kang, Il-Min Kim

A Statistical Framework for Data-dependent Retrieval-Augmented Models

Soumya Basu, Ankit Singh Rawat, Manzil Zaheer

retrieval-augmented modelsdata-dependent retrievalend-to-end trainingexcess risk bounds+2

#83

DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation

Zelin Zang, Hao Luo, Kai Wang et al.

contrastive learningdiffusion modelsdata augmentationunsupervised representation learning+4

#84

Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations

Helen Qu, Sang Michael Xie

domain adaptationout-of-distribution robustnesstargeted data augmentationself-supervised pretraining+4

#85

Extending Test-Time Augmentation with Metamorphic Relations for Combinatorial Problems

Siwei Wei, Xudong Zhang, Zhiyang Zhou et al.

test-time augmentationmetamorphic relationscombinatorial problemsgraph neural networks+3

#86

Not Just Pretty Pictures: Toward Interventional Data Augmentation Using Text-to-Image Generators

Jianhao Yuan, Francesco Pinto, Adam Davies et al.

text-to-image generationsingle domain generalizationspurious feature reductioninterventional data augmentation+4

ICML 2024arXiv:2312.12112

#87

Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes

Nabeel Seedat, Nicolas Huynh, Boris van Breugel et al.

low-data regimestabular data augmentationsynthetic data generationlarge language models+4

#88

First-Order Manifold Data Augmentation for Regression Learning

Ilya Kaufman, Omri Azencot

data augmentationregression learningdomain-independent augmentationtangent plane sampling+3

long-tail instance segmentationgenerative data augmentationdiffusion modelssample efficiency+4

#89

Sample-Efficient Multi-Round Generative Data Augmentation for Long-Tail Instance Segmentation

Byunghyun Kim, Minyoung Bae, Jae-Gil Lee

NeurIPS 2025

NeurIPS 2025arXiv:2510.24262

#90

UtilGen: Utility-Centric Generative Data Augmentation with Dual-Level Task Adaptation

Jiyu Guo, Shuo Yang, Yiming Huang et al.

generative data augmentationtask-specific utilitydual-level optimizationweight allocation network+4

ICLR 2025arXiv:2410.01524

#91

Salient Concept-Aware Generative Data Augmentation

Tianchen Zhao, Xuanbai Chen, Zhihua Li et al.

MASTER: Enhancing Large Language Model via Multi-Agent Simulated Teaching

Liang Yue, Yihong Tang, Kehai Chen et al.

HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models

Seanie Lee, Haebin Seong, Dong Bok Lee et al.

knowledge distillationsafety guard modelsdata augmentationlarge language models+3

NeurIPS 2025arXiv:2406.01899

#94

PANGEA: Projection-Based Augmentation with Non-Relevant General Data for Enhanced Domain Adaptation in LLMs

Seungyoo Lee, Giung Nam, Moonseok Choi et al.

Synthio: Augmenting Small-Scale Audio Classification Datasets with Synthetic Data

Sreyan Ghosh, Sonal Kumar, Zhifeng Kong et al.

Cross-Domain Graph Data Scaling: A Showcase with Diffusion Models

Wenzhuo Tang, Haitao Mao, Danial Dervovic et al.

graph structure augmentationdiffusion modelscross-domain graphsgraph pre-training+2

#97

Generative Data Augmentation via Diffusion Distillation, Adversarial Alignment, and Importance Reweighting

Ruyi An, haicheng huang, Huangjie Zheng et al.

NeurIPS 2025