Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Gadelha, Matheus A."'
Autor:
Son, Sanghyun, Gadelha, Matheus, Zhou, Yang, Fisher, Matthew, Xu, Zexiang, Qiao, Yi-Ling, Lin, Ming C., Zhou, Yi
Recent probabilistic methods for 3D triangular meshes capture diverse shapes by differentiable mesh connectivity, but face high computational costs with increased shape details. We introduce a new differentiable mesh processing method in 2D and 3D th
Externí odkaz:
http://arxiv.org/abs/2412.16776
Autor:
Barda, Amir, Gadelha, Matheus, Kim, Vladimir G., Aigerman, Noam, Bermano, Amit H., Groueix, Thibault
We propose a generative technique to edit 3D shapes, represented as meshes, NeRFs, or Gaussian Splats, in approximately 3 seconds, without the need for running an SDS type of optimization. Our key insight is to cast 3D editing as a multiview image in
Externí odkaz:
http://arxiv.org/abs/2412.00518
Autor:
Pandey, Karran, Gadelha, Matheus, Hold-Geoffroy, Yannick, Singh, Karan, Mitra, Niloy J., Guerrero, Paul
Predicting diverse object motions from a single static image remains challenging, as current video generation models often entangle object movement with camera motion and other scene changes. While recent methods can predict specific motions from mot
Externí odkaz:
http://arxiv.org/abs/2412.00148
Autor:
Chen, Yun-Chun, Ling, Selena, Chen, Zhiqin, Kim, Vladimir G., Gadelha, Matheus, Jacobson, Alec
We propose a novel technique for adding geometric details to an input coarse 3D mesh guided by a text prompt. Our method is composed of three stages. First, we generate a single-view RGB image conditioned on the input coarse geometry and the input te
Externí odkaz:
http://arxiv.org/abs/2406.01592
We present a differentiable representation, DMesh, for general 3D triangular meshes. DMesh considers both the geometry and connectivity information of a mesh. In our design, we first get a set of convex tetrahedra that compactly tessellates the domai
Externí odkaz:
http://arxiv.org/abs/2404.13445
Autor:
Petrov, Dmitry, Goyal, Pradyumn, Thamizharasan, Vikas, Kim, Vladimir G., Gadelha, Matheus, Averkiou, Melinos, Chaudhuri, Siddhartha, Kalogerakis, Evangelos
We introduce GEM3D -- a new deep, topology-aware generative model of 3D shapes. The key ingredient of our method is a neural skeleton-based representation encoding information on both shape topology and geometry. Through a denoising diffusion probabi
Externí odkaz:
http://arxiv.org/abs/2402.16994
Autor:
Cheng, Ta-Ying, Gadelha, Matheus, Groueix, Thibault, Fisher, Matthew, Mech, Radomir, Markham, Andrew, Trigoni, Niki
Current controls over diffusion models (e.g., through text or ControlNet) for image generation fall short in recognizing abstract, continuous attributes like illumination direction or non-rigid shape change. In this paper, we present an approach for
Externí odkaz:
http://arxiv.org/abs/2402.08654
Autor:
Cai, Shengqu, Ceylan, Duygu, Gadelha, Matheus, Huang, Chun-Hao Paul, Wang, Tuanfeng Yang, Wetzstein, Gordon
Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious manual proces
Externí odkaz:
http://arxiv.org/abs/2312.01409
Autor:
Pandey, Karran, Guerrero, Paul, Gadelha, Matheus, Hold-Geoffroy, Yannick, Singh, Karan, Mitra, Niloy
Diffusion Handles is a novel approach to enabling 3D object edits on diffusion images. We accomplish these edits using existing pre-trained diffusion models, and 2D image depth estimation, without any fine-tuning or 3D object retrieval. The edited re
Externí odkaz:
http://arxiv.org/abs/2312.02190
Autor:
Cheng, Ta-Ying, Gadelha, Matheus, Pirk, Soren, Groueix, Thibault, Mech, Radomir, Markham, Andrew, Trigoni, Niki
We present 3DMiner -- a pipeline for mining 3D shapes from challenging large-scale unannotated image datasets. Unlike other unsupervised 3D reconstruction methods, we assume that, within a large-enough dataset, there must exist images of objects with
Externí odkaz:
http://arxiv.org/abs/2310.19188