**UNIMO** is a multi-modal pre-training architecture that can effectively adapt to both single modal and multimodal understanding and generation tasks. UNIMO learns visual representations and textual representations simultaneously, and unifies them into the same semantic space via [cross-modal contrastive learning](https://paperswithcode.com/method/cmcl) (CMCL) based on a large-scale corpus of image collections, text corpus and image-text pairs. The CMCL aligns the visual representation and textual representation, and unifies them into the same semantic
space based on image-text pairs.

**PixelShuffle** is an operation used in super-resolution models to implement efficient sub-pixel convolutions with a stride of $1/r$. Specifically it rearranges elements in a tensor of shape $(\*, C \times r^2, H, W)$ to a tensor of shape $(\*, C, H \times r, W \times r)$.

Image Source: [Remote Sensing Single-Image Resolution Improvement Using A Deep Gradient-Aware Network with Image-Specific Enhancement](https://www.researchgate.net/figure/The-pixel-shuffle-layer-transforms-feature-maps-from-the-LR-domain-to-the-HR-image_fig3_339531308)

PixelShuffle

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

UNIMO

UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning

In the space of adversarial perturbation against classifier accuracy, the ARA is the area between a classifier's curve and the straight line defined by a naive classifier's maximum accuracy. Intuitively, the ARA measures a combination of the classifier’s predictive power and its ability to overcome an adversary. Importantly, when contrasted against existing robustness metrics, the ARA takes into account the classifier’s performance against all adversarial examples, without  bounding them by some arbitrary $\epsilon$.

Source	UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning
Year	2000
Data Source	CC BY-SA - https://paperswithcode.com