An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites
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Updated
Mar 13, 2023
An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites
[NeurIPS‘2021] "TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up", Yifan Jiang, Shiyu Chang, Zhangyang Wang
solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning
Fast inference engine for Transformer models
Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)
Models to perform neural summarization (extractive and abstractive) using machine learning transformers and a tool to convert abstractive summarization datasets to the extractive task.
Based on the Pytorch-Transformers library by HuggingFace. To be used as a starting point for employing Transformer models in text classification tasks. Contains code to easily train BERT, XLNet, RoBERTa, and XLM models for text classification.
[VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.
MinT: Minimal Transformer Library and Tutorials
[BMVC 2022] You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction. SOTA for low light enhancement, 0.004 seconds try this for pre-processing.
How to use our public wav2vec2 dimensional emotion model
Punctuation Restoration using Transformer Models for High-and Low-Resource Languages
The official code repo of "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection"
GRIT: Faster and Better Image-captioning Transformer (ECCV 2022)
The official code repo for "Zero-shot Audio Source Separation through Query-based Learning from Weakly-labeled Data", in AAAI 2022
Tk-Instruct is a Transformer model that is tuned to solve many NLP tasks by following instructions.
Official Repository for the 3DV 2022 paper "The 8-Point Algorithm as an Inductive Bias for Relative Pose Prediction by ViTs"
SignNet and BasisNet
Official release of MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer https://ieeexplore.ieee.org/document/10006398
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