SegGradCAM VS STEGO

Compare SegGradCAM vs STEGO and see what are their differences.

SegGradCAM

SEG-GRAD-CAM: Interpretable Semantic Segmentation via Gradient-Weighted Class Activation Mapping (by kiraving)

STEGO

Unsupervised Semantic Segmentation by Distilling Feature Correspondences (by mhamilton723)
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SegGradCAM STEGO
1 1
94 683
- -
4.2 0.0
8 months ago about 1 year ago
Jupyter Notebook Jupyter Notebook
BSD 3-clause "New" or "Revised" 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.

SegGradCAM

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

STEGO

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

What are some alternatives?

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

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

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

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 ๐Ÿค— transformers. Explain your transformers model in just 2 lines of code.

imodels - Interpretable ML package ๐Ÿ” for concise, transparent, and accurate predictive modeling (sklearn-compatible).

diffusers-interpret - Diffusers-Interpret ๐Ÿค—๐Ÿงจ๐Ÿ•ต๏ธโ€โ™€๏ธ: Model explainability for ๐Ÿค— Diffusers. Get explanations for your generated images.