Deep learning (DL) algorithms have shown significant performance in various computer
vision tasks. However, having limited labelled data lead to a network overfitting problem …

Contrastive pre-training of image-text foundation models such as CLIP demonstrated
excellent zero-shot performance and improved robustness on a wide range of downstream …

Multi-scale resolution training has seen an increased adoption across multiple vision tasks,
including classification and detection. Training with smaller resolutions enables faster …

Contrastive language image pretraining (CLIP) is a standard method for training vision-
language models. While CLIP is scalable, promptable, and robust to distribution shifts on …

Contrastive learning has emerged as a transformative method for learning effective visual
representations through the alignment of image and text embeddings. However, pairwise …

Vision Foundation Models (VFMs) pretrained on massive datasets exhibit impressive
performance on various downstream tasks, especially with limited labeled target data …