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Towards Alias-Free 4D Gaussian Representations with Motion-Aware Filtering
Ankit Dhiman, Kunal A Kathare, Pranav Vignesh +2
Novel-view synthesis of dynamic scenes, crucial for AR/VR applications, remains a challenging problem. Recent methods adapt representations like 3D Gaussian Splatting (3DGS) and Ne…
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…
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…
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…
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 (…