2 citations · 3 across the 10 of their papers we have counts for
10 papers
SeeThrough3D: Occlusion Aware 3D Control in Text-to-Image Generation
Vaibhav Agrawal, Rishubh Parihar, Pradhaan Bhat +2
We identify occlusion reasoning as a fundamental yet overlooked aspect for 3D layout-conditioned generation. It is essential for synthesizing partially occluded objects with depth-…
GeoDiv: Framework For Measuring Geographical Diversity In Text-To-Image Models
Abhipsa Basu, Mohana Singh, Shashank Agnihotri +2
Text-to-image (T2I) models are rapidly gaining popularity, yet their outputs often lack geographical diversity, reinforce stereotypes, and misrepresent regions. Given their broad r…
MirrorVerse: Pushing Diffusion Models to Realistically Reflect the World
Ankit Dhiman, Manan Shah, R Venkatesh Babu
Diffusion models have become central to various image editing tasks, yet they often fail to fully adhere to physical laws, particularly with effects like shadows, reflections, and…
Turbo-GS: Accelerating 3D Gaussian Fitting for High-Quality Radiance Fields
Ankit Dhiman, Tao Lu, R Srinath +5
Novel-view synthesis plays a crucial role in computer vision with applications in 3D reconstruction, mixed reality, and robotics. Recent approaches, such as 3D Gaussian Splatting (…
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…
Exploring Attribute Variations in Style-based GANs using Diffusion Models
Rishubh Parihar, Prasanna Balaji, Raghav Magazine +4
Existing attribute editing methods treat semantic attributes as binary, resulting in a single edit per attribute. However, attributes such as eyeglasses, smiles, or hairstyles exhi…
ChromaDistill: Colorizing Monochrome Radiance Fields with Knowledge Distillation
Ankit Dhiman, R Srinath, Srinjay Sarkar +2
Colorization is a well-explored problem in the domains of image and video processing. However, extending colorization to 3D scenes presents significant challenges. Recent Neural Ra…