46 citations · 59 across the 7 of their papers we have counts for
7 papers
Are Diffusion Models Vision-And-Language Reasoners?
Benno Krojer, Elinor Poole-Dayan, Vikram Voleti +2
Text-conditioned image generation models have recently shown immense qualitative success using denoising diffusion processes. However, unlike discriminative vision-and-language mod…
Controllable Image Generation via Collage Representations
Arantxa Casanova, Marlène Careil, Adriana Romero-Soriano +3
Recent advances in conditional generative image models have enabled impressive results. On the one hand, text-based conditional models have achieved remarkable generation quality,…
Score-based Diffusion Models in Function Space
Jae Hyun Lim, Nikola B. Kovachki, Ricardo Baptista +10
Diffusion models have recently emerged as a powerful framework for generative modeling. They consist of a forward process that perturbs input data with Gaussian white noise and a r…
Score-based Denoising Diffusion with Non-Isotropic Gaussian Noise Models
Vikram Voleti, Christopher Pal, Adam Oberman
Generative models based on denoising diffusion techniques have led to an unprecedented increase in the quality and diversity of imagery that is now possible to create with neural g…
SMPL-IK: Learned Morphology-Aware Inverse Kinematics for AI Driven Artistic Workflows
Vikram Voleti, Boris N. Oreshkin, Florent Bocquelet +3
Inverse Kinematics (IK) systems are often rigid with respect to their input character, thus requiring user intervention to be adapted to new skeletons. In this paper we aim at crea…
MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation
Vikram Voleti, Alexia Jolicoeur-Martineau, Christopher Pal
Video prediction is a challenging task. The quality of video frames from current state-of-the-art (SOTA) generative models tends to be poor and generalization beyond the training d…
Multi-Resolution Continuous Normalizing Flows
Vikram Voleti, Chris Finlay, Adam Oberman +1
Recent work has shown that Neural Ordinary Differential Equations (ODEs) can serve as generative models of images using the perspective of Continuous Normalizing Flows (CNFs). Such…