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Ruofan Liang (若凡, RF)
Ph.D. Candidate |
About
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I am a final-year PhD student at the University of Toronto, supervised by Prof. Nandita Vijaykumar, and affiliated with the Vector Institute.
I was a research intern at Meta Reality Labs in Zurich, and previously at NVIDIA Toronto AI Lab.
My current research interests are in computer vision and graphics, including but not limited
neural rendering, inverse rendering, generative models, and 3D reconstruction tasks.
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News
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Research
LuxRemix: Lighting Decomposition and Remixing for Indoor Scenes
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LuxDiT: Lighting Estimation with Video Diffusion Transformer
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UniRelight: Learning Joint Decomposition and Synthesis for Video Relighting
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Controllable Weather Synthesis and Removal with Video Diffusion Models
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ContraGS: Codebook-Condensed and Trainable Gaussian Splatting for Fast, Memory-Efficient Reconstruction
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VideoMat: Extracting PBR Materials from Video Diffusion Models
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DiffusionRenderer: Neural Inverse and Forward Rendering with Video Diffusion Models
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Retri3D: 3D Neural Graphics Representation Retrieval
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Photorealistic Object Insertion with Diffusion-Guided Inverse Rendering
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SCAR: Sub-Core and Atomic-Unit Collaborative Reduction for Efficient Raster-based Differentiable Rendering
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INRet: A General Framework for Accurate Retrieval of INRs for Shapes
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GaussianObject: Just Taking Four Images to Get A High-Quality 3D Object with Gaussian Splatting
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DISORF: A Distributed Online 3D Reconstruction Framework for Mobile Robots
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ENVIDR: Implicit Differentiable Renderer with Neural Environment Lighting
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SPIDR: SDF-based Neural Point Fields for Illumination and Deformation |
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CoordX: Accelerating Implicit Neural Representation with a Split MLP Architecture |
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Knowledge Consistency between Neural Networks and Beyond |
Previous Projects
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Accel-RF |
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FPGA RAM Mapper |
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Tetris-RL |
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Accel-Video Pipe (AVPipe) |
Miscellaneous
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I am a geek always excited to discover something Fun.
Now, I am still on my long long way to obtaining knowledge & experience,
hoping to exploit my potential.
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Put on a happy face🙃~ |