SegGradCAM
SEG-GRAD-CAM: Interpretable Semantic Segmentation via Gradient-Weighted Class Activation Mapping (by kiraving)
rankseg
[JMLR 2023] RankSEG: A consistent ranking-based framework for segmentation (by statmlben)
SegGradCAM | rankseg | |
---|---|---|
1 | 1 | |
94 | 15 | |
- | - | |
4.2 | 4.6 | |
8 months ago | 8 months 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.
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.
-
Negative gradients when calculating GradCAM heatmap
Code for https://arxiv.org/abs/2002.11434 found: https://github.com/kiraving/SegGradCAM
rankseg
Posts with mentions or reviews of rankseg.
We have used some of these posts to build our list of alternatives
and similar projects.
-
[R] RankSEG: A Consistent Ranking-based Framework for Segmentation
Github website: https://github.com/statmlben/rankseg
What are some alternatives?
When comparing SegGradCAM and rankseg 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.
notebooks - Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.