3 citations · 3 across the 1 of their papers we have counts for
4 papers
Manifold Sampling for Differentiable Uncertainty in Radiance Fields
Linjie Lyu, Ayush Tewari, Marc Habermann +4
Radiance fields are powerful and, hence, popular models for representing the appearance of complex scenes. Yet, constructing them based on image observations gives rise to ambiguit…
Diffusion Posterior Illumination for Ambiguity-aware Inverse Rendering
Linjie Lyu, Ayush Tewari, Marc Habermann +4
Inverse rendering, the process of inferring scene properties from images, is a challenging inverse problem. The task is ill-posed, as many different scene configurations can give r…
ROAM: Robust and Object-Aware Motion Generation Using Neural Pose Descriptors
Wanyue Zhang, Rishabh Dabral, Thomas Leimkühler +3
Existing automatic approaches for 3D virtual character motion synthesis supporting scene interactions do not generalise well to new objects outside training distributions, even whe…
End-to-end Sampling Patterns
Thomas Leimkühler, Gurprit Singh, Karol Myszkowski +2
Sample patterns have many uses in Computer Graphics, ranging from procedural object placement over Monte Carlo image synthesis to non-photorealistic depiction. Their properties suc…