Zobrazeno 1 - 10
of 235
pro vyhledávání: '"Novotný, David"'
Autor:
Bensadoun, Raphael, Monnier, Tom, Kleiman, Yanir, Kokkinos, Filippos, Siddiqui, Yawar, Kariya, Mahendra, Harosh, Omri, Shapovalov, Roman, Graham, Benjamin, Garreau, Emilien, Karnewar, Animesh, Cao, Ang, Azuri, Idan, Makarov, Iurii, Le, Eric-Tuan, Toisoul, Antoine, Novotny, David, Gafni, Oran, Neverova, Natalia, Vedaldi, Andrea
We introduce Meta 3D Gen (3DGen), a new state-of-the-art, fast pipeline for text-to-3D asset generation. 3DGen offers 3D asset creation with high prompt fidelity and high-quality 3D shapes and textures in under a minute. It supports physically-based
Externí odkaz:
http://arxiv.org/abs/2407.02599
Autor:
Siddiqui, Yawar, Monnier, Tom, Kokkinos, Filippos, Kariya, Mahendra, Kleiman, Yanir, Garreau, Emilien, Gafni, Oran, Neverova, Natalia, Vedaldi, Andrea, Shapovalov, Roman, Novotny, David
We present Meta 3D AssetGen (AssetGen), a significant advancement in text-to-3D generation which produces faithful, high-quality meshes with texture and material control. Compared to works that bake shading in the 3D object's appearance, AssetGen out
Externí odkaz:
http://arxiv.org/abs/2407.02445
Contemporary 3D research, particularly in reconstruction and generation, heavily relies on 2D images for inputs or supervision. However, current designs for these 2D-3D mapping are memory-intensive, posing a significant bottleneck for existing method
Externí odkaz:
http://arxiv.org/abs/2404.19760
We present a method to build animatable dog avatars from monocular videos. This is challenging as animals display a range of (unpredictable) non-rigid movements and have a variety of appearance details (e.g., fur, spots, tails). We develop an approac
Externí odkaz:
http://arxiv.org/abs/2403.17103
Autor:
Höllein, Lukas, Božič, Aljaž, Müller, Norman, Novotny, David, Tseng, Hung-Yu, Richardt, Christian, Zollhöfer, Michael, Nießner, Matthias
3D asset generation is getting massive amounts of attention, inspired by the recent success of text-guided 2D content creation. Existing text-to-3D methods use pretrained text-to-image diffusion models in an optimization problem or fine-tune them on
Externí odkaz:
http://arxiv.org/abs/2403.01807
Autor:
Karnewar, Animesh, Shapovalov, Roman, Monnier, Tom, Vedaldi, Andrea, Mitra, Niloy J., Novotny, David
Encoding information from 2D views of an object into a 3D representation is crucial for generalized 3D feature extraction. Such features can then enable 3D reconstruction, 3D generation, and other applications. We propose GOEmbed (Gradient Origin Emb
Externí odkaz:
http://arxiv.org/abs/2312.08744
Structure-from-motion (SfM) is a long-standing problem in the computer vision community, which aims to reconstruct the camera poses and 3D structure of a scene from a set of unconstrained 2D images. Classical frameworks solve this problem in an incre
Externí odkaz:
http://arxiv.org/abs/2312.04563