8 papers
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…
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…