6 papers
YouDream: Generating Anatomically Controllable Consistent Text-to-3D Animals
Sandeep Mishra, Oindrila Saha, Alan C. Bovik
3D generation guided by text-to-image diffusion models enables the creation of visually compelling assets. However previous methods explore generation based on image or text. The b…
Decomposed evaluations of geographic disparities in text-to-image models
Abhishek Sureddy, Dishant Padalia, Nandhinee Periyakaruppa +6
Recent work has identified substantial disparities in generated images of different geographic regions, including stereotypical depictions of everyday objects like houses and cars.…
C3DAG: Controlled 3D Animal Generation using 3D pose guidance
Sandeep Mishra, Oindrila Saha, Alan C. Bovik
Recent advancements in text-to-3D generation have demonstrated the ability to generate high quality 3D assets. However while generating animals these methods underperform, often po…
Improved Zero-Shot Classification by Adapting VLMs with Text Descriptions
Oindrila Saha, Grant Van Horn, Subhransu Maji
The zero-shot performance of existing vision-language models (VLMs) such as CLIP is limited by the availability of large-scale, aligned image and text datasets in specific domains.…
PARTICLE: Part Discovery and Contrastive Learning for Fine-grained Recognition
Oindrila Saha, Subhransu Maji
We develop techniques for refining representations for fine-grained classification and segmentation tasks in a self-supervised manner. We find that fine-tuning methods based on ins…
GANORCON: Are Generative Models Useful for Few-shot Segmentation?
Oindrila Saha, Zezhou Cheng, Subhransu Maji
Advances in generative modeling based on GANs has motivated the community to find their use beyond image generation and editing tasks. In particular, several recent works have show…