April 26, 2024, 4:45 a.m. | Parul Gupta, Munawar Hayat, Abhinav Dhall, Thanh-Toan Do

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.16556v1 Announce Type: new
Abstract: Few-shot image synthesis entails generating diverse and realistic images of novel categories using only a few example images. While multiple recent efforts in this direction have achieved impressive results, the existing approaches are dependent only upon the few novel samples available at test time in order to generate new images, which restricts the diversity of the generated images. To overcome this limitation, we propose Conditional Distribution Modelling (CDM) -- a framework which effectively utilizes Diffusion …

abstract arxiv cs.cv diffusion diffusion models distribution diverse example few-shot image images modelling multiple novel results samples synthesis test type while

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Sr. Software Development Manager, AWS Neuron Machine Learning Distributed Training

@ Amazon.com | Cupertino, California, USA