130 citations · 217 across the 33 of their papers we have counts for
35 papers
RefDiT: Local Attribute Guidance in Reference-Based Image Generation
Rameshwar Mishra, Srikrishna Karanam, A V Subramanyam
Personalization models generate new images guided by a few subject references, while style transfer methods aim to produce images aligned with a global style derived from a referen…
SafaRi:Adaptive Sequence Transformer for Weakly Supervised Referring Expression Segmentation
Sayan Nag, Koustava Goswami, Srikrishna Karanam
Referring Expression Segmentation (RES) aims to provide a segmentation mask of the target object in an image referred to by the text (i.e., referring expression). Existing methods…
AlignIT: Enhancing Prompt Alignment in Customization of Text-to-Image Models
Aishwarya Agarwal, Srikrishna Karanam, Balaji Vasan Srinivasan
We consider the problem of customizing text-to-image diffusion models with user-supplied reference images. Given new prompts, the existing methods can capture the key concept from…
Composing Parts for Expressive Object Generation
Harsh Rangwani, Aishwarya Agarwal, Kuldeep Kulkarni +2
Image composition and generation are processes where the artists need control over various parts of the generated images. However, the current state-of-the-art generation models, l…
Few Shot Class Incremental Learning using Vision-Language models
Anurag Kumar, Chinmay Bharti, Saikat Dutta +2
Recent advancements in deep learning have demonstrated remarkable performance comparable to human capabilities across various supervised computer vision tasks. However, the prevale…
Approximate Caching for Efficiently Serving Diffusion Models
Shubham Agarwal, Subrata Mitra, Sarthak Chakraborty +3
Text-to-image generation using diffusion models has seen explosive popularity owing to their ability in producing high quality images adhering to text prompts. However, production-…