STEGO VS SegGradCAM

Compare STEGO vs SegGradCAM and see what are their differences.

STEGO

Unsupervised Semantic Segmentation by Distilling Feature Correspondences (by mhamilton723)
Computer Vision Deep Learning iclr2022 Pytorch semantic-segmentation unsupervised-learning
Source Code
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SegGradCAM

SEG-GRAD-CAM: Interpretable Semantic Segmentation via Gradient-Weighted Class Activation Mapping (by kiraving)
explainable-ai explainable-ml Computer Vision Segmentation semantic-segmentation
Source Code
ojs.aaai.org
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STEGO SegGradCAM
1 1
683 94
- -
0.0 4.2
about 1 year ago 8 months ago
Jupyter Notebook Jupyter Notebook
MIT License BSD 3-clause "New" or "Revised" 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.

STEGO

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

SegGradCAM

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

What are some alternatives?

When comparing STEGO and SegGradCAM you can also consider the following projects:

rankseg - [JMLR 2023] RankSEG: A consistent ranking-based framework for segmentation

super-gradients - Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.

pytorch-segmentation - :art: Semantic segmentation models, datasets and losses implemented in PyTorch.

OmniXAI - OmniXAI: A Library for eXplainable AI

transformers-interpret - Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

imodels - Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

diffusers-interpret - Diffusers-Interpret 🤗🧨🕵️‍♀️: Model explainability for 🤗 Diffusers. Get explanations for your generated images.

STEGO vs rankseg SegGradCAM vs super-gradients STEGO vs pytorch-segmentation SegGradCAM vs rankseg SegGradCAM vs OmniXAI SegGradCAM vs transformers-interpret SegGradCAM vs imodels SegGradCAM vs diffusers-interpret