2022
Exploring Plain Vision Transformer Backbones for Object Detection
Investigating the effectiveness of plain Vision Transformers as backbones for object detection and proposing modifications to improve their performance.
Tagged with
transformers
Explore machine learning papers and reviews related to transformers. Find insights, analysis, and implementation details.
7
Papers Found
Papers Related to transformers
2020
End-to-End Object Detection with Transformers
Introducing DETR, a novel end-to-end object detection framework that leverages Transformers to directly predict a set of object bounding boxes.
2021
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Introducing Vision Transformer (ViT), a pure transformer architecture for image recognition that achieves state-of-the-art results.
2023
A Survey of Techniques for Optimizing Transformer Inference
TransformersInference OptimizationPruningQuantizationKnowledge DistillationNeural Architecture SearchHardware Acceleration
A comprehensive survey of techniques for optimizing the inference phase of transformer networks.
2021
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Introducing Swin Transformer, a hierarchical Vision Transformer that uses shifted windows to achieve improved efficiency and performance in various vision tasks.
2017
Attention Is All You Need
A deep dive into the revolutionary Transformer architecture paper that changed the landscape of deep learning.
2021
Data Movement Is All You Need: A Case Study on Optimizing Transformers
A case study on optimizing transformers by focusing on data movement