awesome-semantic-segmentation VS LLM-eval-survey

Compare awesome-semantic-segmentation vs LLM-eval-survey and see what are their differences.

LLM-eval-survey

The official GitHub page for the survey paper "A Survey on Evaluation of Large Language Models". (by MLGroupJLU)
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awesome-semantic-segmentation LLM-eval-survey
1 1
10,337 1,240
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0.0 9.2
about 3 years ago 5 months ago
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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.

awesome-semantic-segmentation

Posts with mentions or reviews of awesome-semantic-segmentation. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-28.
  • Instance Segmentation
    3 projects | /r/computervision | 28 Aug 2021
    Here is an amazing compilation of code and papers on segmentation: https://github.com/mrgloom/awesome-semantic-segmentation

LLM-eval-survey

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

What are some alternatives?

When comparing awesome-semantic-segmentation and LLM-eval-survey you can also consider the following projects:

detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

awesome-refreshing-llms - EMNLP'23 survey: a curation of awesome papers and resources on refreshing large language models (LLMs) without expensive retraining.

U-2-Net - The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."

deepmark - Deepmark AI enables a unique testing environment for language models (LLM) assessment on task-specific metrics and on your own data so your GenAI-powered solution has predictable and reliable performance.

semantic-kitti-api - SemanticKITTI API for visualizing dataset, processing data, and evaluating results.

ai-topics - Hot topics on AI

pycm - Multi-class confusion matrix library in Python

Tools-to-Design-or-Visualize-Architecture-of-Neural-Network - Tools to Design or Visualize Architecture of Neural Network

PPM - A High-Quality Photograpy Portrait Matting Benchmark