SparK VS SimMIM

Compare SparK vs SimMIM and see what are their differences.

SparK

[ICLR'23 Spotlight🔥] The first successful BERT/MAE-style pretraining on any convolutional network; Pytorch impl. of "Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling" (by keyu-tian)

SimMIM

This is an official implementation for "SimMIM: A Simple Framework for Masked Image Modeling". (by microsoft)
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SparK SimMIM
3 1
1,388 860
- 0.0%
7.3 0.0
3 months ago over 1 year ago
Python Python
MIT License MIT License
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.

SparK

Posts with mentions or reviews of SparK. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-17.

SimMIM

Posts with mentions or reviews of SimMIM. We have used some of these posts to build our list of alternatives and similar projects.
  • My DL model mis-segment wrong objects with similar colors
    1 project | /r/computervision | 20 Mar 2023
    It seems the segmentation task is complex. One thing that I can suggest that definitely worked for me is Self-supervised learning prior to training. The task of the sel-supervision is very important. In your case I suggest Masked Image Modeling because it does not rely heavily on shapes and colors but can leverage them if they exist. Check out SimMIM by Microsoft. https://arxiv.org/abs/2111.09886 . https://github.com/microsoft/simmim

What are some alternatives?

When comparing SparK and SimMIM you can also consider the following projects:

SincNet - SincNet is a neural architecture for efficiently processing raw audio samples.

Unsupervised-Classification - SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]

mmselfsup - OpenMMLab Self-Supervised Learning Toolbox and Benchmark

mmdetection - OpenMMLab Detection Toolbox and Benchmark

cnnimageretrieval-pytorch - CNN Image Retrieval in PyTorch: Training and evaluating CNNs for Image Retrieval in PyTorch

PaddleClas - A treasure chest for visual classification and recognition powered by PaddlePaddle

DeepMalwareDetector - A Deep Learning framework that analyses Windows PE files to detect malicious Softwares.

Swin-Transformer - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".