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20202026
most citedGET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images

187 citations · 294 across the 31 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

cs.CV2025

ChronoEdit: Towards Temporal Reasoning for Image Editing and World Simulation

Jay Zhangjie Wu, Xuanchi Ren, Tianchang Shen +11

Recent advances in large generative models have greatly enhanced both image editing and in-context image generation, yet a critical gap remains in ensuring physical consistency, wh…

cs.CR2025

MarkDiffusion: An Open-Source Toolkit for Generative Watermarking of Latent Diffusion Models

Leyi Pan, Sheng Guan, Zheyu Fu +9

We introduce MarkDiffusion, an open-source Python toolkit for generative watermarking of latent diffusion models. It comprises three key components: a unified implementation framew…

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

VideoMat: Extracting PBR Materials from Video Diffusion Models

Jacob Munkberg, Zian Wang, Ruofan Liang +2

We leverage finetuned video diffusion models, intrinsic decomposition of videos, and physically-based differentiable rendering to generate high quality materials for 3D models give…

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★ 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…