Year: 2024
Type: preprint
Abstract: Our work aims to build a model that performs dual tasks of image captioning and image generation while being trained on only one task. The central idea is to train an invertible model that learns a one-to-one mapping between the image and text embeddings. Once the invertible model is efficiently trained on one task, the image captioning, the same model can generate new images for a given text through the inversion process, with no additional training. This paper proposes a simple invertible neural network architecture for this problem and presents our current findings.
Source: arXiv (Cornell University)
Authors: Menon, Nandakishore S, Kamanchi, Chandramouli, Diddigi, Raghuram Bharadwaj
Institution: IBM (India)
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4404313774