activity
20192022
most citedHuman Motion Diffusion Model

168 citations · 286 across the 14 of their papers we have counts for

collaborators

20 papers

cs.CV2022168 cited

Human Motion Diffusion Model

Guy Tevet, Sigal Raab, Brian Gordon +3

Natural and expressive human motion generation is the holy grail of computer animation. It is a challenging task, due to the diversity of possible motion, human perceptual sensitiv…

cs.SD20225 cited

Unaligned Supervision For Automatic Music Transcription in The Wild

Ben Maman, Amit H. Bermano

Multi-instrument Automatic Music Transcription (AMT), or the decoding of a musical recording into semantic musical content, is one of the holy grails of Music Information Retrieval…

cs.CV2022

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…

cs.CV20229 cited

State-of-the-Art in the Architecture, Methods and Applications of StyleGAN

Amit H. Bermano, Rinon Gal, Yuval Alaluf +5

Generative Adversarial Networks (GANs) have established themselves as a prevalent approach to image synthesis. Of these, StyleGAN offers a fascinating case study, owing to its rema…

cs.CV20223 cited

Self-Conditioned Generative Adversarial Networks for Image Editing

Yunzhe Liu, Rinon Gal, Amit H. Bermano +2

Generative Adversarial Networks (GANs) are susceptible to bias, learned from either the unbalanced data, or through mode collapse. The networks focus on the core of the data distri…

cs.GR202211 cited

CLIPasso: Semantically-Aware Object Sketching

Yael Vinker, Ehsan Pajouheshgar, Jessica Y. Bo +5

Abstraction is at the heart of sketching due to the simple and minimal nature of line drawings. Abstraction entails identifying the essential visual properties of an object or scen…