Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Ranade, Siddhant"'
Autor:
Ranade, Siddhant, Lassner, Christoph, Li, Kai, Haene, Christian, Chen, Shen-Chi, Bazin, Jean-Charles, Bouaziz, Sofien
Neural Radiance Fields (NeRFs) encode the radiance in a scene parameterized by the scene's plenoptic function. This is achieved by using an MLP together with a mapping to a higher-dimensional space, and has been proven to capture scenes with a great
Externí odkaz:
http://arxiv.org/abs/2212.03406
We propose a novel technique to register sparse 3D scans in the absence of texture. While existing methods such as KinectFusion or Iterative Closest Points (ICP) heavily rely on dense point clouds, this task is particularly challenging under sparse c
Externí odkaz:
http://arxiv.org/abs/2010.02516
Recovering 3D human pose from 2D joints is a highly unconstrained problem. We propose a novel neural network framework, PoseNet3D, that takes 2D joints as input and outputs 3D skeletons and SMPL body model parameters. By casting our learning approach
Externí odkaz:
http://arxiv.org/abs/2003.03473
Popular 3D scan registration projects, such as Stanford digital Michelangelo or KinectFusion, exploit the high-resolution sensor data for scan alignment. It is particularly challenging to solve the registration of sparse 3D scans in the absence of RG
Externí odkaz:
http://arxiv.org/abs/1906.05888
Autor:
Lin, Hubert, Averkiou, Melinos, Kalogerakis, Evangelos, Kovacs, Balazs, Ranade, Siddhant, Kim, Vladimir G., Chaudhuri, Siddhartha, Bala, Kavita
Material understanding is critical for design, geometric modeling, and analysis of functional objects. We enable material-aware 3D shape analysis by employing a projective convolutional neural network architecture to learn material- aware descriptors
Externí odkaz:
http://arxiv.org/abs/1810.08729
Autor:
Ranade, Siddhant, Ramalingam, Srikumar
This paper proposes a novel and exact method to reconstruct line-based 3D structure from a single image using Manhattan world assumption. This problem is a distinctly unsolved problem because there can be multiple 3D reconstructions from a single ima
Externí odkaz:
http://arxiv.org/abs/1810.03737
Autor:
Mateus, André1 (AUTHOR), Ranade, Siddhant2 (AUTHOR), Ramalingam, Srikumar3 (AUTHOR), Miraldo, Pedro4 (AUTHOR) miraldo@merl.com
Publikováno v:
International Journal of Computer Vision. Aug2023, Vol. 131 Issue 8, p2044-2069. 26p.
