visual-inductive-priors-for-data-efficient-dl-w.md

ICCVW-2023-Papers

Application

4th Visual Inductive Priors for Data-Efficient Deep Learning Workshop

Title	Repo	Paper	Video
Using and Abusing Equivariance	➖		➖
Video BagNet: Short Temporal Receptive Fields Increase Robustness in Long-Term Action Recognition			➖
COSE: A Consistency-Sensitivity Metric for Saliency on Image Classification			➖
DFM-X: Augmentation by Leveraging Prior Knowledge of Shortcut Learning			➖
Good Fences Make Good Neighbours	➖		➖
Data Efficient Single Image Dehazing via Adversarial Auto-Augmentation and Extended Atmospheric Scattering Model	➖		➖
Distilling Part-Whole Hierarchical Knowledge from a Huge Pretrained Class Agnostic Segmentation Framework			➖
Padding Aware Neurons	➖		➖
Logarithm-Transform Aided Gaussian Sampling for Few-Shot Learning			➖
DeepVAT: A Self-Supervised Technique for Cluster Assessment in Image Datasets	➖		➖
No Data Augmentation? Alternative Regularizations for Effective Training on Small Datasets	➖		➖
RV-VAE: Integrating Random Variable Algebra into Variational Autoencoders			➖
PARTICLE: Part Discovery and Contrastive Learning for Fine-Grained Recognition			➖
Self-Supervised Learning of Contextualized Local Visual Embeddings			➖
InterAug: A Tuning-Free Augmentation Policy for Data-Efficient and Robust Object Detection			➖
Geometric Superpixel Representations for Efficient Image Classification with Graph Neural Networks			➖
Geometric Contrastive Learning	➖		➖