3 papers
cs.CV2026
Probability-Flow Distillation: Exact Wasserstein Gradient Flow for High-Fidelity 3D Generation
Rohith Ramanan, A. N. Rajagopalan
Score Distillation Sampling (SDS) and its variants have been widely used for text-to-3D generation by distilling 2D image diffusion priors. However, the standard SDS objective is p…
cs.CV2024
PNeRV: A Polynomial Neural Representation for Videos
Sonam Gupta, Snehal Singh Tomar, Grigorios G Chrysos +2
Extracting Implicit Neural Representations (INRs) on video data poses unique challenges due to the additional temporal dimension. In the context of videos, INRs have predominantly…
cs.CV2023
Latents2Semantics: Leveraging the Latent Space of Generative Models for Localized Style Manipulation of Face Images
Snehal Singh Tomar, A. N. Rajagopalan
With the metaverse slowly becoming a reality and given the rapid pace of developments toward the creation of digital humans, the need for a principled style editing pipeline for hu…