562 citations · 899 across the 4 of their papers we have counts for
4 papers
Segment Anything
Alexander Kirillov, Eric Mintun, Nikhila Ravi +9
We introduce the Segment Anything (SA) project: a new task, model, and dataset for image segmentation. Using our efficient model in a data collection loop, we built the largest seg…
A ConvNet for the 2020s
Zhuang Liu, Hanzi Mao, Chao-Yuan Wu +3
The "Roaring 20s" of visual recognition began with the introduction of Vision Transformers (ViTs), which quickly superseded ConvNets as the state-of-the-art image classification mo…
Exploring Plain Vision Transformer Backbones for Object Detection
Yanghao Li, Hanzi Mao, Ross Girshick +1
We explore the plain, non-hierarchical Vision Transformer (ViT) as a backbone network for object detection. This design enables the original ViT architecture to be fine-tuned for o…
Entailment as Few-Shot Learner
Sinong Wang, Han Fang, Madian Khabsa +2
Large pre-trained language models (LMs) have demonstrated remarkable ability as few-shot learners. However, their success hinges largely on scaling model parameters to a degree tha…