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