Search Results for author:
Found 4 papers, 4 papers with code
Entailment as Few-Shot Learner
Large pre-trained language models (LMs) have demonstrated remarkable ability as few-shot learners.
Ranked #1 on
Topic Classification
on OS
A ConvNet for the 2020s
The "Roaring 20s" of visual recognition began with the introduction of Vision Transformers (ViTs), which quickly superseded ConvNets as the state-of-the-art image classification model.
Ranked #1 on
Classification
on InDL
Exploring Plain Vision Transformer Backbones for Object Detection
This design enables the original ViT architecture to be fine-tuned for object detection without needing to redesign a hierarchical backbone for pre-training.
Ranked #5 on
Instance Segmentation
on LVIS v1.0 val
Segment Anything
We introduce the Segment Anything (SA) project: a new task, model, and dataset for image segmentation.
Ranked #2 on
Zero-Shot Instance Segmentation
on LVIS v1.0 val
