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
Vision Transformer (ViT) explained: how splitting images into 16x16 patches enables pure transformer architecture for state-of-the-art image recognition.
2023
A Survey of Techniques for Optimizing Transformer Inference
TransformersInference OptimizationPruningQuantizationKnowledge DistillationNeural Architecture SearchHardware Acceleration
Survey of transformer inference optimization: pruning, quantization, knowledge distillation, neural architecture search, and hardware acceleration.
2021
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Swin Transformer: hierarchical Vision Transformer using shifted windows for efficient image classification, object detection, and segmentation.
2017
Attention Is All You Need
Deep dive into the Transformer architecture that revolutionized NLP. Understand self-attention, multi-head attention, and positional encoding.
2021
Data Movement Is All You Need: A Case Study on Optimizing Transformers
Analysis of transformer performance bottlenecks caused by data movement. Learn optimization strategies for memory-bound operations on GPUs.