CeiT VS dytox

Compare CeiT vs dytox and see what are their differences.

dytox

Dynamic Token Expansion with Continual Transformers, accepted at CVPR 2022 (by arthurdouillard)
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CeiT dytox
1 1
95 132
- -
0.0 1.8
about 3 years ago almost 2 years ago
Python Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

CeiT

Posts with mentions or reviews of CeiT. We have used some of these posts to build our list of alternatives and similar projects.

dytox

Posts with mentions or reviews of dytox. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing CeiT and dytox you can also consider the following projects:

vit-pytorch - Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

ml-cvnets - CVNets: A library for training computer vision networks

T2T-ViT - ICCV2021, Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

Efficient-AI-Backbones - Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.

efficientnet - Implementation of EfficientNet model. Keras and TensorFlow Keras.

EfficientFormer - EfficientFormerV2 [ICCV 2023] & EfficientFormer [NeurIPs 2022]

MLP-Mixer-pytorch - Unofficial implementation of MLP-Mixer: An all-MLP Architecture for Vision