Data Augmentation
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Benchmarks
Most implemented
YOLOv4: Optimal Speed and Accuracy of Object Detection
Improved Baselines with Momentum Contrastive Learning
AutoAugment: Learning Augmentation Policies from Data
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
Improved Regularization of Convolutional Neural Networks with Cutout
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
Papers
Det-LIME: Detector-Aware, Multi-Instance Local Interpretable Model-Agnostic Explanations for Automated Marine Mammal Detection
Despite the rapid uptake of black-box object detectors in marine mammal research and monitoring, explainability techniques are rarely integrated into conservation workflows. Furthermore, most classification-oriented expl…
Data AugmentationIsotropic Embedding Perturbations for Robust Vision Language Encoders
Data augmentation is fundamental to training modern deep vision and multimodal models. While individual methods, such as RandAug, CutMix, Mixup, RandErase, and DropPath, offer strong regularization effects, their combine…
Data AugmentationHessian-based molecular conformation augmentation for a scalable and efficient strategy of machine learning interatomic potentials
While machine-learning interatomic potentials (MLIPs) have successfully learned potential energy surfaces (PES) and atomic forces, many practical applications, such as vibrational analysis and transition state search, re…
Data AugmentationREER-PT: Reverse-Engineered Reasoning for Perplexity-Guided Pre-training Data Augmentation
As language-model compute continues to scale, high-quality training data is becoming an increasingly important bottleneck. Conventional next-token prediction supervises what follows a context but leaves the intermediate …
Data AugmentationAQ3D: Adaptive Query Transformer for 3D Instance Segmentation
Transformer-based decoders for 3D instance segmentation typically commit to a fixed number of queries and positional modeling calibrated on the training distribution rather than on the scene at hand. Indoor scans vary wi…
3D Instance SegmentationData AugmentationCross-Spectral Dense Correspondence for Multimodal Spectral Medical Imaging
Precise dense correspondence is a fundamental prerequisite for multimodal spectral imaging systems that fuse disparate wavelength ranges for subsequent analysis in medical and scientific imaging. Corresponding image poin…
Data Augmentation