9 citations · 17 across the 15 of their papers we have counts for
4 papers · 2 filters
ImPoster: Text and Frequency Guidance for Subject Driven Action Personalization using Diffusion Models
Divya Kothandaraman, Kuldeep Kulkarni, Sumit Shekhar +2
We present ImPoster, a novel algorithm for generating a target image of a 'source' subject performing a 'driving' action. The inputs to our algorithm are a single pair of a source…
3D-free meets 3D priors: Novel View Synthesis from a Single Image with Pretrained Diffusion Guidance
Taewon Kang, Divya Kothandaraman, Dinesh Manocha +1
Recent 3D novel view synthesis (NVS) methods often require extensive 3D data for training, and also typically lack generalization beyond the training distribution. Moreover, they t…
Text Prompting for Multi-Concept Video Customization by Autoregressive Generation
Divya Kothandaraman, Kihyuk Sohn, Ruben Villegas +3
We present a method for multi-concept customization of pretrained text-to-video (T2V) models. Intuitively, the multi-concept customized video can be derived from the (non-linear) i…
Financial Models in Generative Art: Black-Scholes-Inspired Concept Blending in Text-to-Image Diffusion
Divya Kothandaraman, Ming Lin, Dinesh Manocha
We introduce a novel approach for concept blending in pretrained text-to-image diffusion models, aiming to generate images at the intersection of multiple text prompts. At each tim…