VICRegL: Self-Supervised Learning of Local Visual Features

Understand

Most recent self-supervised methods for learning image representations focus on either producing a global feature with invariance properties, or producing a set of local features.

• The former works best for classification tasks while the latter is best for detection and segmentation tasks.
• This paper explores the fundamental trade-off between learning local and global features.
• A new method called VICRegL is proposed that learns good global and local features simultaneously, yielding excellent performance on detection and segmentation tasks while maintaining good performance on classification tasks.