55 citations · 94 across the 4 of their papers we have counts for
9 papers
Null-text Inversion for Editing Real Images using Guided Diffusion Models
Ron Mokady, Amir Hertz, Kfir Aberman +2
Recent text-guided diffusion models provide powerful image generation capabilities. Currently, a massive effort is given to enable the modification of these images using text only…
MotionCLIP: Exposing Human Motion Generation to CLIP Space
Guy Tevet, Brian Gordon, Amir Hertz +2
We introduce MotionCLIP, a 3D human motion auto-encoder featuring a latent embedding that is disentangled, well behaved, and supports highly semantic textual descriptions. MotionCL…
SPAGHETTI: Editing Implicit Shapes Through Part Aware Generation
Amir Hertz, Or Perel, Raja Giryes +2
Neural implicit fields are quickly emerging as an attractive representation for learning based techniques. However, adopting them for 3D shape modeling and editing is challenging.…
Mesh Draping: Parametrization-Free Neural Mesh Transfer
Amir Hertz, Or Perel, Raja Giryes +2
Despite recent advances in geometric modeling, 3D mesh modeling still involves a considerable amount of manual labor by experts. In this paper, we introduce Mesh Draping: a neural…
SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization
Amir Hertz, Or Perel, Raja Giryes +2
Multilayer-perceptrons (MLP) are known to struggle with learning functions of high-frequencies, and in particular cases with wide frequency bands. We present a spatially adaptive p…
Deep Geometric Texture Synthesis
Amir Hertz, Rana Hanocka, Raja Giryes +1
Recently, deep generative adversarial networks for image generation have advanced rapidly; yet, only a small amount of research has focused on generative models for irregular struc…