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Found 8 papers, 1 papers with code
Gaussian Splatting in Style
Scene stylization extends the work of neural style transfer to three spatial dimensions.
Urban-StyleGAN: Learning to Generate and Manipulate Images of Urban Scenes
Moreover, we employ an unsupervised latent exploration algorithm in the $\mathcal{S}$-space of the generator and show that it is more efficient than the conventional $\mathcal{W}^{+}$-space in controlling the image content.
SupeRVol: Super-Resolution Shape and Reflectance Estimation in Inverse Volume Rendering
We propose an end-to-end inverse rendering pipeline called SupeRVol that allows us to recover 3D shape and material parameters from a set of color images in a super-resolution manner.
Implicit Shape Completion via Adversarial Shape Priors
Finally, we show that our adversarial training approach leads to visually plausible reconstructions that are highly consistent in recovering missing parts of a given object.
FIRe: Fast Inverse Rendering using Directional and Signed Distance Functions
To this end, we learn a signed distance function (SDF) along with our DDF model to represent a class of shapes.
Joint Deep Multi-Graph Matching and 3D Geometry Learning from Inhomogeneous 2D Image Collections
While these approaches mainly focus on learning node and edge attributes, they completely ignore the 3D geometry of the underlying 3D objects depicted in the 2D images.
Ranked #11 on
Graph Matching
on PASCAL VOC
i3DMM: Deep Implicit 3D Morphable Model of Human Heads
Our approach has the following favorable properties: (i) It is the first full head morphable model that includes hair.
Convex Optimisation for Inverse Kinematics
We consider the problem of inverse kinematics (IK), where one wants to find the parameters of a given kinematic skeleton that best explain a set of observed 3D joint locations.
