81 citations · 150 across the 48 of their papers we have counts for
11 papers · 1 filter
Sparse Code Uplifting for Efficient 3D Language Gaussian Splatting
Lovre Antonio Budimir, Yushi Guan, Steve Ryhner +2
3D Language Gaussian Splatting (3DLGS) augments 3D Gaussian Splatting with language-aligned visual features for open-vocabulary 3D scene understanding. A core challenge is efficien…
MERG3R: A Divide-and-Conquer Approach to Large-Scale Neural Visual Geometry
Leo Kaixuan Cheng, Abdus Shaikh, Ruofan Liang +3
Recent advancements in neural visual geometry, including transformer-based models such as VGGT and Pi3, have achieved impressive accuracy on 3D reconstruction tasks. However, their…
LuxRemix: Lighting Decomposition and Remixing for Indoor Scenes
Ruofan Liang, Norman Müller, Ethan Weber +4
We present a novel approach for interactive light editing in indoor scenes from a single multi-view scene capture. Our method leverages a generative image-based light decomposition…
FG-Attn: Leveraging Fine-Grained Sparse Attention in Video Diffusion Models
Sankeerth Durvasula, Kavya Sreedhar, Zain Moustafa +6
Using diffusion transformers for media generation may require evaluating attention over extremely long sequences, with attention layers accounting for the majority of generation la…
UniRelight: Learning Joint Decomposition and Synthesis for Video Relighting
Kai He, Ruofan Liang, Jacob Munkberg +7
We address the challenge of relighting a single image or video, a task that demands precise scene intrinsic understanding and high-quality light transport synthesis. Existing end-t…
DiffusionRenderer: Neural Inverse and Forward Rendering with Video Diffusion Models
Ruofan Liang, Zan Gojcic, Huan Ling +8
Understanding and modeling lighting effects are fundamental tasks in computer vision and graphics. Classic physically-based rendering (PBR) accurately simulates the light transport…
Photorealistic Object Insertion with Diffusion-Guided Inverse Rendering
Ruofan Liang, Zan Gojcic, Merlin Nimier-David +4
The correct insertion of virtual objects in images of real-world scenes requires a deep understanding of the scene's lighting, geometry and materials, as well as the image formatio…
DISTWAR: Fast Differentiable Rendering on Raster-based Rendering Pipelines
Sankeerth Durvasula, Adrian Zhao, Fan Chen +3
Differentiable rendering is a technique used in an important emerging class of visual computing applications that involves representing a 3D scene as a model that is trained from 2…
ENVIDR: Implicit Differentiable Renderer with Neural Environment Lighting
Ruofan Liang, Huiting Chen, Chunlin Li +3
Recent advances in neural rendering have shown great potential for reconstructing scenes from multiview images. However, accurately representing objects with glossy surfaces remain…
SPIDR: SDF-based Neural Point Fields for Illumination and Deformation
Ruofan Liang, Jiahao Zhang, Haoda Li +3
Neural radiance fields (NeRFs) have recently emerged as a promising approach for 3D reconstruction and novel view synthesis. However, NeRF-based methods encode shape, reflectance,…
CoordX: Accelerating Implicit Neural Representation with a Split MLP Architecture
Ruofan Liang, Hongyi Sun, Nandita Vijaykumar
Implicit neural representations with multi-layer perceptrons (MLPs) have recently gained prominence for a wide variety of tasks such as novel view synthesis and 3D object represent…