MPViT
how-do-vits-work
| MPViT | how-do-vits-work | |
|---|---|---|
| 1 | 3 | |
| 340 | 784 | |
| - | - | |
| 1.8 | 0.0 | |
| about 2 years ago | almost 2 years ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
MPViT
-
[P] MPViT : Multi-Path Vision Transformer for Dense Prediction
code : https://github.com/youngwanLEE/MPViT
how-do-vits-work
-
A New Deep Learning Study Investigate and Clarify the Intrinsic Behavior of Transformers in Computer Vision
Github: https://github.com/xxxnell/how-do-vits-work
-
[D] Paper Explained – How Do Vision Transformers Work?
Code for https://arxiv.org/abs/2202.06709 found: https://github.com/xxxnell/how-do-vits-work
- How Do Vision Transformers Work?
What are some alternatives?
LaTeX-OCR - pix2tex: Using a ViT to convert images of equations into LaTeX code.
Parallel-Tacotron2 - PyTorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling
Efficient-AI-Backbones - Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
awesome-fast-attention - list of efficient attention modules
AutoML - This is a collection of our NAS and Vision Transformer work. [Moved to: https://github.com/microsoft/Cream]
mmdetection - OpenMMLab Detection Toolbox and Benchmark
scenic - Scenic: A Jax Library for Computer Vision Research and Beyond
vit-explain - Explainability for Vision Transformers
Cream - This is a collection of our NAS and Vision Transformer work. [Moved to: https://github.com/microsoft/AutoML]
query-selector - LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION
attention_to_gif - Visualize transition of attention weights across layers in a Transformer as a GIF