11 citations · 40 across the 36 of their papers we have counts for
4 papers · 1 filter
Compact Neural Graphics Primitives with Learned Hash Probing
Towaki Takikawa, Thomas Müller, Merlin Nimier-David +4
Neural graphics primitives are faster and achieve higher quality when their neural networks are augmented by spatial data structures that hold trainable features arranged in a grid…
Adaptive Shells for Efficient Neural Radiance Field Rendering
Zian Wang, Tianchang Shen, Merlin Nimier-David +6
Neural radiance fields achieve unprecedented quality for novel view synthesis, but their volumetric formulation remains expensive, requiring a huge number of samples to render high…
WildFusion: Learning 3D-Aware Latent Diffusion Models in View Space
Katja Schwarz, Seung Wook Kim, Jun Gao +3
Modern learning-based approaches to 3D-aware image synthesis achieve high photorealism and 3D-consistent viewpoint changes for the generated images. Existing approaches represent i…
TexFusion: Synthesizing 3D Textures with Text-Guided Image Diffusion Models
Tianshi Cao, Karsten Kreis, Sanja Fidler +2
We present TexFusion (Texture Diffusion), a new method to synthesize textures for given 3D geometries, using large-scale text-guided image diffusion models. In contrast to recent w…