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Jeff Tan
Hello! I am a first-year CS PhD student at Stanford University, fortunate to be working with Prof. Jiajun Wu. Previously, I completed my MS in Robotics and undergrad in CS at Carnegie Mellon University, advised by Prof. Deva Ramanan. I am grateful to be supported by the NSF Graduate Research Fellowship (2023-).
I am interested in 3D/4D computer vision and its intersection with robotics, physical simulation, and generative AI.
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MonoFusion: Sparse-View 4D Reconstruction via Monocular Fusion
Zihan Wang,
Jeff Tan,
Tarasha Khurana,
Neehar Peri,
Deva Ramanan
ICCV 2025
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arXiv |
Github
We reconstruct dynamic human-centric scenes (e.g. playing the piano and bicycle repair) from sparse-view video.
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DiffusionSfM: Predicting Structure and Motion via Ray Origin and Endpoint Diffusion
Qitao Zhao,
Amy Lin,
Jeff Tan,
Jason Y. Zhang,
Deva Ramanan,
Shubham Tulsiani
CVPR 2025
Website |
arXiv |
Github
From a set of multi-view images, we learn a denoising diffusion model that outputs scene geometry and cameras in global frame.
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DressRecon: Freeform 4D Human Reconstruction from Monocular Video
Jeff Tan,
Donglai Xiang,
Shubham Tulsiani,
Deva Ramanan,
Gengshan Yang
3DV 2025 (Oral)
Website |
arXiv |
Github
From a single monocular video, we reconstruct humans in loose clothing and interacting with objects, using a hierarchical deformation field and image-based priors.
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Distilling Neural Fields for Real-Time Articulated Shape Reconstruction
Jeff Tan,
Gengshan Yang,
Deva Ramanan
CVPR 2023
Website |
Paper |
Github
We learn real-time feed-forward pose and shape predictors, by distilling knowledge from offline differentiable rendering optimizers.
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Credits to Jon Barron for this website's template.
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