Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Dahnert, Manuel"'
We present a novel diffusion-based approach for coherent 3D scene reconstruction from a single RGB image. Our method utilizes an image-conditioned 3D scene diffusion model to simultaneously denoise the 3D poses and geometries of all objects within th
Externí odkaz:
http://arxiv.org/abs/2412.10294
Understanding 3D scenes from a single image is fundamental to a wide variety of tasks, such as for robotics, motion planning, or augmented reality. Existing works in 3D perception from a single RGB image tend to focus on geometric reconstruction only
Externí odkaz:
http://arxiv.org/abs/2111.02444
3D scan geometry and CAD models often contain complementary information towards understanding environments, which could be leveraged through establishing a mapping between the two domains. However, this is a challenging task due to strong, lower-leve
Externí odkaz:
http://arxiv.org/abs/1908.06989
Visualizing time series in a dense spatial context such as a geographical map is a challenging task, which requires careful balance between the amount of depicted data and perceptual precision. Horizon graphs are a well-known technique for compactly
Externí odkaz:
http://arxiv.org/abs/1906.07377
Autor:
Avetisyan, Armen, Dahnert, Manuel, Dai, Angela, Savva, Manolis, Chang, Angel X., Nießner, Matthias
We present Scan2CAD, a novel data-driven method that learns to align clean 3D CAD models from a shape database to the noisy and incomplete geometry of a commodity RGB-D scan. For a 3D reconstruction of an indoor scene, our method takes as input a set
Externí odkaz:
http://arxiv.org/abs/1811.11187
Autor:
Noeckel, James1 (AUTHOR), Zhao, Haisen1,2 (AUTHOR), Curless, Brian1 (AUTHOR), Schulz, Adriana1 (AUTHOR)
Publikováno v:
Computer Graphics Forum. Aug2021, Vol. 40 Issue 5, p301-314. 14p. 7 Color Photographs, 3 Diagrams, 1 Chart.
