Sotabase

Career

· Masters Student in Computer Science, Stanford University2025–
· PhD Student of Biosystem Engineering, Michigan State University2023–
· PhD in Computer Science, Stanford University2022–
· Senior Image Algorithm Engineer, MissFresh2018–2022
· Software Engineer, DLODLO2016–2018
· Bachelor of Engineering in Electronic Science and Technology, Beijing University of Posts and Telecommunications2012–2016
· Research Intern, Google Brain Toronto
· Research Intern, Google DeepMind
· Research Scientist, Waymo Research

Publications (39)

NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis
Computer Vision and Pattern Recognition · 2020
673
cited
CvxNet: Learnable Convex Decomposition
Computer Vision and Pattern Recognition · 2019
277
cited
NASA: Neural Articulated Shape Approximation
European Conference on Computer Vision · 2019
225
cited
Offboard 3D Object Detection from Point Cloud Sequences
Computer Vision and Pattern Recognition · 2021
202
cited
NeRFactor
ACM Transactions on Graphics · 2021
180
cited
BlockQNN: Efficient Block-Wise Neural Network Architecture Generation
IEEE Transactions on Pattern Analysis and Machine Intelligence · 2018
131
cited
Peephole: Predicting Network Performance Before Training
arXiv.org · 2017
111
cited
Canonical Capsules: Unsupervised Capsules in Canonical Pose
Neural Information Processing Systems · 2020
44
cited
GINA-3D: Learning to Generate Implicit Neural Assets in the Wild
Computer Vision and Pattern Recognition · 2023
31
cited
Revisiting 3D Object Detection From an Egocentric Perspective
Neural Information Processing Systems · 2021
26
cited
LumiGAN: Unconditional Generation of Relightable 3D Human Faces
International Conference on 3D Vision · 2023
23
cited
Unsupervised Learning of Shape Programs with Repeatable Implicit Parts
Neural Information Processing Systems · 2022
17
cited
Robust Symmetry Detection via Riemannian Langevin Dynamics
ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia · 2024
13
cited
Cerberus: A Multi-headed Derenderer
arXiv.org · 2019
8
cited
Unleashing the Potential of CNNs for Interpretable Few-Shot Learning
arXiv.org · 2017
4
cited
Few-shot Learning by Exploiting Visual Concepts within CNNs
2017
3
cited
Adding New Categories in Object Detection Using Few-Shot Copy-Paste
2022
Cerberus : A Multiheaded Derenderer
2019
Hierarchical Deep Recurrent Architecture for Video Understanding
arXiv.org · 2017
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