22 citations · 25 across the 17 of their papers we have counts for
4 papers · 2 filters
Reflecting Reality: Enabling Diffusion Models to Produce Faithful Mirror Reflections
Ankit Dhiman, Manan Shah, Rishubh Parihar +3
We tackle the problem of generating highly realistic and plausible mirror reflections using diffusion-based generative models. We formulate this problem as an image inpainting task…
PreciseControl: Enhancing Text-To-Image Diffusion Models with Fine-Grained Attribute Control
Rishubh Parihar, Sachidanand VS, Sabariswaran Mani +2
Recently, we have seen a surge of personalization methods for text-to-image (T2I) diffusion models to learn a concept using a few images. Existing approaches, when used for face pe…
Text2Place: Affordance-aware Text Guided Human Placement
Rishubh Parihar, Harsh Gupta, Sachidanand VS +1
For a given scene, humans can easily reason for the locations and pose to place objects. Designing a computational model to reason about these affordances poses a significant chall…
Balancing Act: Distribution-Guided Debiasing in Diffusion Models
Rishubh Parihar, Abhijnya Bhat, Abhipsa Basu +3
Diffusion Models (DMs) have emerged as powerful generative models with unprecedented image generation capability. These models are widely used for data augmentation and creative ap…