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cover of episode Effortless 2D-Guided, 3D Gaussian Segmentation: Related Work

Effortless 2D-Guided, 3D Gaussian Segmentation: Related Work

2024/6/6
logo of podcast Machine Learning Tech Brief By HackerNoon

Machine Learning Tech Brief By HackerNoon

Shownotes Transcript

This story was originally published on HackerNoon at: https://hackernoon.com/effortless-2d-guided-3d-gaussian-segmentation-related-work). Efficient 3D Gaussian segmentation guided by 2D models achieves fast, accurate multi-object segmentation, advancing 3D scene understanding and editing. Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning). You can also check exclusive content about #machine-learning), #gaussian-clustering), #3d-gaussian-segmentation), #3d-scene-understanding), #2d-to-3d-supervision), #ai-in-3d-graphics), #semantic-information-learning), #point-based-rendering), and more.

        This story was written by: [@escholar](https://hackernoon.com/u/escholar)). Learn more about this writer by checking [@escholar's](https://hackernoon.com/about/escholar)) about page,
        and for more stories, please visit [hackernoon.com](https://hackernoon.com)).
        
            
            
            3D Gaussian, a recently proposed explicit representation method, has attained remarkable achievements in three-dimensional scene reconstruction. Using a series of scene images and corresponding camera data, it employs 3D Gaussians to depict scene objects. Gaussian Splatting then utilizes point-based rendering for efficient 3D to 2D projection.