120 citations · 183 across the 15 of their papers we have counts for
15 papers
PRedItOR: Text Guided Image Editing with Diffusion Prior
Hareesh Ravi, Sachin Kelkar, Midhun Harikumar +1
Diffusion models have shown remarkable capabilities in generating high quality and creative images conditioned on text. An interesting application of such models is structure prese…
Enhanced Controllability of Diffusion Models via Feature Disentanglement and Realism-Enhanced Sampling Methods
Wonwoong Cho, Hareesh Ravi, Midhun Harikumar +5
As Diffusion Models have shown promising performance, a lot of efforts have been made to improve the controllability of Diffusion Models. However, how to train Diffusion Models to…
Controlled and Conditional Text to Image Generation with Diffusion Prior
Pranav Aggarwal, Hareesh Ravi, Naveen Marri +12
Denoising Diffusion models have shown remarkable performance in generating diverse, high quality images from text. Numerous techniques have been proposed on top of or in alignment…
Uncovering the Disentanglement Capability in Text-to-Image Diffusion Models
Qiucheng Wu, Yujian Liu, Handong Zhao +6
Generative models have been widely studied in computer vision. Recently, diffusion models have drawn substantial attention due to the high quality of their generated images. A key…
Fine-grained Image Captioning with CLIP Reward
Jaemin Cho, Seunghyun Yoon, Ajinkya Kale +3
Modern image captioning models are usually trained with text similarity objectives. However, since reference captions in public datasets often describe the most salient common obje…
StyleBabel: Artistic Style Tagging and Captioning
Dan Ruta, Andrew Gilbert, Pranav Aggarwal +9
We present StyleBabel, a unique open access dataset of natural language captions and free-form tags describing the artistic style of over 135K digital artworks, collected via a nov…