activity
20182026
most citedLION: Latent Point Diffusion Models for 3D Shape Generation

190 citations · 595 across the 39 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

cs.CV2025

SimULi: Real-Time LiDAR and Camera Simulation with Unscented Transforms

Haithem Turki, Qi Wu, Xin Kang +5

Rigorous testing of autonomous robots, such as self-driving vehicles, is essential to ensure their safety in real-world deployments. This requires building high-fidelity simulators…

cs.CV2025

Lyra: Generative 3D Scene Reconstruction via Video Diffusion Model Self-Distillation

Sherwin Bahmani, Tianchang Shen, Jiawei Ren +10

The ability to generate virtual environments is crucial for applications ranging from gaming to physical AI domains such as robotics, autonomous driving, and industrial AI. Current…

cs.GR2025★ 1 cited

LuxDiT: Lighting Estimation with Video Diffusion Transformer

Ruofan Liang, Kai He, Zan Gojcic +4

Estimating scene lighting from a single image or video remains a longstanding challenge in computer vision and graphics. Learning-based approaches are constrained by the scarcity o…

cs.CV2025

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…

cs.GR2025

Controllable Weather Synthesis and Removal with Video Diffusion Models

Chih-Hao Lin, Zian Wang, Ruofan Liang +4

Generating realistic and controllable weather effects in videos is valuable for many applications. Physics-based weather simulation requires precise reconstructions that are hard t…

cs.CV2025

Difix3D+: Improving 3D Reconstructions with Single-Step Diffusion Models

Jay Zhangjie Wu, Yuxuan Zhang, Haithem Turki +6

Neural Radiance Fields and 3D Gaussian Splatting have revolutionized 3D reconstruction and novel-view synthesis task. However, achieving photorealistic rendering from extreme novel…

cs.CV2025★ 1 cited

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…