Awesome Scene Understanding
A curated list of research papers and resources for scene understanding in computer vision, covering 3D reconstruction, layout estimation, and primitive detection.
What is Awesome Scene Understanding?
Awesome Scene Understanding is a curated GitHub repository that aggregates academic papers, datasets, and resources for the field of 3D scene understanding in computer vision. It helps researchers and developers find the latest methods for tasks like reconstructing room layouts from images, parsing 3D structures, and working with related datasets. The project organizes a vast amount of research to provide a clear overview of the state-of-the-art.
Computer vision researchers, PhD students, and engineers specializing in 3D reconstruction, geometric deep learning, or robotics who need a structured reference for academic literature and public datasets.
It saves significant time in literature review by providing a meticulously organized and community-maintained list of papers, complete with links to code and datasets. Unlike generic paper lists, it focuses specifically on the holistic and geometric understanding of scenes.
Overview
😎 A list of awesome scene understanding papers.
Use Cases
Best For
- Finding benchmark datasets for indoor 3D scene understanding tasks
Related Projects
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