75 citations · 75 across the 5 of their papers we have counts for
5 papers
iNVS: Repurposing Diffusion Inpainters for Novel View Synthesis
Yash Kant, Aliaksandr Siarohin, Michael Vasilkovsky +4
We present a method for generating consistent novel views from a single source image. Our approach focuses on maximizing the reuse of visible pixels from the source image. To achie…
Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors
Guocheng Qian, Jinjie Mai, Abdullah Hamdi +8
We present Magic123, a two-stage coarse-to-fine approach for high-quality, textured 3D meshes generation from a single unposed image in the wild using both2D and 3D priors. In the…
Invertible Neural Skinning
Yash Kant, Aliaksandr Siarohin, Riza Alp Guler +4
Building animatable and editable models of clothed humans from raw 3D scans and poses is a challenging problem. Existing reposing methods suffer from the limited expressiveness of…
3D generation on ImageNet
Ivan Skorokhodov, Aliaksandr Siarohin, Yinghao Xu +4
Existing 3D-from-2D generators are typically designed for well-curated single-category datasets, where all the objects have (approximately) the same scale, 3D location, and orienta…
Unsupervised Volumetric Animation
Aliaksandr Siarohin, Willi Menapace, Ivan Skorokhodov +5
We propose a novel approach for unsupervised 3D animation of non-rigid deformable objects. Our method learns the 3D structure and dynamics of objects solely from single-view RGB vi…