| _ | mixup | _ |
|---|
| Adaptive Semi-Supervised | mixup | with Implicit Label Learning and Sample Ratio Balancing |
| Adversarial | mixup | Ratio Confusion for Unsupervised Domain Adaptation |
| Adversarial Vertex | mixup | : Toward Better Adversarially Robust Generalization |
| AutoMix: | mixup | Networks for Sample Interpolation via Cooperative Barycenter Learning |
| AutoMix: Unveiling the Power of | mixup | for Stronger Classifiers |
| Boosting Covid-19 Severity Detection with Infection-aware Contrastive | mixup | Classification |
| Charting the Right Manifold: Manifold | mixup | for Few-shot Learning |
| CMC-COV19D: Contrastive | mixup | Classification for COVID-19 Diagnosis |
| Computation-Efficient Knowledge Distillation via Uncertainty-Aware | mixup | |
| Confusion | mixup | Regularized Multimodal Fusion Network for Continual Egocentric Activity Recognition |
| Context-Aware | mixup | for Domain Adaptive Semantic Segmentation |
| DBN-Mix: Training dual branch network using bilateral | mixup | augmentation for long-tailed visual recognition |
| Decoupled | mixup | for Out-of-distribution Visual Recognition |
| Domain Adaptation using Self-Training with | mixup | for One-Stage Object Detection |
| Domain Generalization with Global Sample | mixup | |
| Dual | mixup | Regularized Learning for Adversarial Domain Adaptation |
| F- | mixup | : Attack CNNs From Fourier Perspective |
| Few-Shot Domain Adaptation via | mixup | Optimal Transport |
| Few-Shot Image Generation with | mixup | -Based Distance Learning |
| Generalizable Medical Image Segmentation via Random Amplitude | mixup | and Domain-Specific Image Restoration |
| Generalizing Person Re-identification by Camera-aware Invariance Learning and Cross-Domain | mixup | |
| Improving Robustness of Deep Learning Based Knee MRI Segmentation: | mixup | and Adversarial Domain Adaptation |
| Intelligent and Adaptive | mixup | Technique for Adversarial Robustness |
| Inter-domain | mixup | for semi-supervised domain adaptation |
| Introducing Competition to Boost the Transferability of Targeted Adversarial Examples Through Clean Feature | mixup | |
| Learn to Threshold: ThresholdNet With Confidence-Guided Manifold | mixup | for Polyp Segmentation |
| MixAugment & | mixup | : Augmentation Methods for Facial Expression Recognition |
| MixCycle: | mixup | Assisted Semi-Supervised 3D Single Object Tracking with Cycle Consistency |
| MixSKD: Self-Knowledge Distillation from | mixup | for Image Recognition |
| MixSpeech: Cross-Modality Self-Learning with Audio-Visual Stream | mixup | for Visual Speech Translation and Recognition |
| mixup | Asymmetric Tri-Training for Heartbeat Classification Under Domain Shift |
| mixup | Data Augmentation for COVID-19 Infection Percentage Estimation |
| mixup | gamblers+: Learning interpolated pseudo uncertainty in latent feature space for reliable inference |
| mixup | -Based Deep Metric Learning Approaches for Incomplete Supervision |
| Multi-scale self-attention | mixup | for graph classification |
| Neural Networks Are More Productive Teachers Than Human Raters: Active | mixup | for Data-Efficient Knowledge Distillation From a Blackbox Model |
| New Data Augmentation Method Based on | mixup | and Dempster-Shafer Theory, A |
| OccluMix: Towards De-Occlusion Virtual Try-on by Semantically-Guided | mixup | |
| On the Pitfall of | mixup | for Uncertainty Calibration |
| Progressive | mixup | Augmented Teacher-Student Learning for Unsupervised Domain Adaptation |
| Pseudo-Bag | mixup | Augmentation for Multiple Instance Learning-Based Whole Slide Image Classification |
| Rank | mixup | : Ranking-Based Mixup Training for Network Calibration |
| Recall@k Surrogate Loss with Large Batches and Similarity | mixup | |
| ROAM: Random layer | mixup | for semi-supervised learning in medical images |
| SegMix: Co-occurrence Driven | mixup | for Semantic Segmentation and Adversarial Robustness |
| SimpliMix: A Simplified Manifold | mixup | for Few-shot Point Cloud Classification |
| Understanding the Role of | mixup | in Knowledge Distillation: An Empirical Study |
| Vision-Language Navigation with Random Environmental | mixup | |
| VQAMix: Conditional Triplet | mixup | for Medical Visual Question Answering |
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