Ruijie Lu

Ruijie Lu (陆睿杰)

I'm currently a second-year Ph.D student at Peking University (PKU), supervised by Prof. Gang Zeng. Before that, I received by Bachelor's degree at Peking University in July 2023. My research interests lie in 3D Computer Vision, especially scene understanding, generation and reconstruction.

Email / Google Scholar / Github

Research

	TACO: Taming Diffusion for in-the-wild Video Amodal Completion Ruijie Lu, Yixin Chen, Yu Liu, Jiaxiang Tang, Junfeng Ni, Diwen Wan, Gang Zeng, Siyuan Huang ICCV 2025 [Paper] [Code] [Data] [Project Page] We introduce TACO, which repurposes pre-trained video diffusion models for Video Amodal Completion (VAC), facilitating downstream tasks like reconstruction. The key insight lies in the data curation and progressive training strategy.
	MOVIS: Enhancing Multi-Object Novel View Synthesis for Indoor Scenes Ruijie Lu, Yixin Chen, Junfeng Ni, Baoxiong Jia, Yu Liu, Diwen Wan, Gang Zeng, Siyuan Huang CVPR 2025 [Paper] [Code] [Data] [Project Page] We introduce MOVIS, which repurposes pre-trained diffusion models for multi-object level novel view synthesis (NVS) in indoor scenes. The key insight lies in incorporating a structure-aware noise scheduler and an auxiliary mask prediction task under novel views.
	RoomTex: Texturing Compositional Indoor Scenes via Iterative Inpainting Qi Wang, Ruijie Lu, Xudong Xu, Jingbo Wang, Michael Yu Wang, Bo Dai, Gang Zeng, Dan Xu ECCV 2024 [Paper] [Code] [Project Page] We introduce RoomTex, which utilizes image inpainting to synthesize high-quality and style-consistent textures of multiple styles given scene meshes.
	Decompositional Neural Scene Reconstruction with Generative Diffusion Prior Junfeng Ni, Yu Liu, Ruijie Lu, Zirui Zhou, Song-Chun Zhu, Yixin Chen, Siyuan Huang CVPR 2025 [Paper] [Project Page] [Code] We introduce DP-Recon, a novel approach that distills off-the-shelf diffusion models for high-quality decompositional scene reconstruction from sparse view images. Further fine-grained editings are well supported.
	Building Interactable Replicas of Complex Articulated Objects via Gaussian Splatting Yu Liu, Baoxiong Jia, Ruijie Lu, Junfeng Ni, Song-Chun Zhu, Siyuan Huang ICLR 2025 [Paper] [Project Page] [Code] We introduce ArtGS, a novel approach that leverages 3D Gaussians to reconstruct articulated objects from 2 states of RGBD images, which achieves state-of-the-art performance in joint parameter estimation and part mesh reconstruction.
	Superpoint Gaussian Splatting for Real-Time High-Fidelity Dynamic Scene Reconstruction Diwen Wan, Ruijie Lu, Gang Zeng, ICML 2024 [Paper] [Code] [Project Page] We introduce SP-GS, which utilizes superpoint to represent neighboring Gaussians with similar motion patterns for efficiency.
	InTeX: Interactive Text-to-Texture Synthesis via Unified Depth-aware Inpainting Jiaxiang Tang, Ruijie Lu, Hang Zhou, Xiang Wen, Xiaokang Chen, Diwen Wan, Gang Zeng, Jingdong Wang, Ziwei Liu, arXiv [Paper] [Code] [Project Page] We introduce InTeX, which utilizes depth-aware inpainting to synthesize high-quality textures from text prompts for objects.

Experience

	Peking University, China 2023.09 - now Ph.D. Student Advisor: Prof. Gang Zeng
	Beijing Institute for General Artificial Intelligence (BIGAI), China 2023.12 - now Research Intern Advisor: Dr. Yixin Chen and Dr. Siyuan Huang
	Shanghai Artificial Intelligence Laboratory, China 2023.06 - 2023.11 Research Intern Advisor: Dr. Xudong Xu and Dr. Jingbo Wang
	Peking University, China 2019.09 - 2023.07 Undergraduate Student

Fell free to contact me if you have any problem.
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