MIO: A Foundation Model on Multimodal Tokens
Paper • 2409.17692 • Published • 53
Transformer-based Models for Computer Vision
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An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Paper • 2010.11929 • Published • 21 -
Going deeper with Image Transformers
Paper • 2103.17239 • Published -
Training data-efficient image transformers & distillation through attention
Paper • 2012.12877 • Published • 2 -
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Paper • 2103.14030 • Published • 5 -
Masked Autoencoders Are Scalable Vision Learners
Paper • 2111.06377 • Published • 6 -
DINOv2: Learning Robust Visual Features without Supervision
Paper • 2304.07193 • Published • 10 -
Emerging Properties in Self-Supervised Vision Transformers
Paper • 2104.14294 • Published • 4 -
BEiT: BERT Pre-Training of Image Transformers
Paper • 2106.08254 • Published • 2 -
Learning Transferable Visual Models From Natural Language Supervision
Paper • 2103.00020 • Published • 22 -
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers
Paper • 2106.10270 • Published • 3 -
Biomedical SAM 2: Segment Anything in Biomedical Images and Videos
Paper • 2408.03286 • Published -
SAM 2: Segment Anything in Images and Videos
Paper • 2408.00714 • Published • 123