5 citations · 8 across the 6 of their papers we have counts for
6 papers
Generative Lifting of Multiview to 3D from Unknown Pose: Wrapping NeRF inside Diffusion
Xin Yuan, Rana Hanocka, Michael Maire
We cast multiview reconstruction from unknown pose as a generative modeling problem. From a collection of unannotated 2D images of a scene, our approach simultaneously learns both…
AmbiGen: Generating Ambigrams from Pre-trained Diffusion Model
Boheng Zhao, Rana Hanocka, Raymond A. Yeh
Ambigrams are calligraphic designs that have different meanings depending on the viewing orientation. Creating ambigrams is a challenging task even for skilled artists, as it requi…
HyperFields: Towards Zero-Shot Generation of NeRFs from Text
Sudarshan Babu, Richard Liu, Avery Zhou +3
We introduce HyperFields, a method for generating text-conditioned Neural Radiance Fields (NeRFs) with a single forward pass and (optionally) some fine-tuning. Key to our approach…
GeoCode: Interpretable Shape Programs
Ofek Pearl, Itai Lang, Yuhua Hu +2
The task of crafting procedural programs capable of generating structurally valid 3D shapes easily and intuitively remains an elusive goal in computer vision and graphics. Within t…
LoopDraw: a Loop-Based Autoregressive Model for Shape Synthesis and Editing
Nam Anh Dinh, Haochen Wang, Greg Shakhnarovich +1
There is no settled universal 3D representation for geometry with many alternatives such as point clouds, meshes, implicit functions, and voxels to name a few. In this work, we pre…
TetGAN: A Convolutional Neural Network for Tetrahedral Mesh Generation
William Gao, April Wang, Gal Metzer +2
We present TetGAN, a convolutional neural network designed to generate tetrahedral meshes. We represent shapes using an irregular tetrahedral grid which encodes an occupancy and di…