7 papers
AdaptiveSplat:Texture Aware Controllable 3D Gaussian Allocation for Feed-Forward Reconstruction
Badrinath Singhal, Srihari K G, Sreehari Iyer +2
Current feed-forward 3D reconstruction methods predict pixel aligned Gaussian primitives, resulting in highly redundant representations. A natural solution is to prune the redundan…
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 (…
UniC-Lift: Unified 3D Instance Segmentation via Contrastive Learning
Ankit Dhiman, Srinath R, Jaswanth Reddy +2
3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) have advanced novel-view synthesis. Recent methods extend multi-view 2D segmentation to 3D, enabling instance/semanti…
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…
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…
Instructive3D: Editing Large Reconstruction Models with Text Instructions
Kunal Kathare, Ankit Dhiman, K Vikas Gowda +4
Transformer based methods have enabled users to create, modify, and comprehend text and image data. Recently proposed Large Reconstruction Models (LRMs) further extend this by prov…