MengyangPu/RINDNet
RINDNet: Edge Detection for Discontinuity in Reflectance, Illumination, Normal and Depth, in ICCV 2021 (oral)
This project helps computer vision researchers and practitioners accurately detect various types of edges in images. It takes standard image files as input and outputs detailed maps highlighting different edge categories: those caused by changes in surface reflectance, illumination, surface normal, and depth. This tool is designed for anyone working on advanced image analysis, scene understanding, or 3D reconstruction who needs a precise understanding of object boundaries and surface properties.
126 stars. No commits in the last 6 months.
Use this if you need to identify and categorize specific types of edges in images, beyond just generic boundary detection.
Not ideal if you only need basic object detection or segmentation, as this tool focuses specifically on the nuanced classification of edge types.
Stars
126
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18
Language
Python
License
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Last pushed
Sep 28, 2022
Commits (30d)
0
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