Nana Wang   王楠

I am a Second-year Computer Science Master's student at CAD Research Center, Tongji University.

My research interests focus on 3D Vision(Neural rendering, 3dgs, Multi View Stereo, etc).

If you find any research interests that we might share, feel free to drop me an email. I am always open to potential collaborations.

Email  /  CV  /  Google Scholar  /  Github /  Linkedin

中文 / English
 日本語(learning)/ français(learning)

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Short Bio
I am a M.Sc student in Computer Science at CAD Research Center, Tongji University.

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Research

Much of my research is about inferring the physical world (shape, motion, color, light, etc) from images and 3D raw data. Representative papers are highlighted.

A Real2Sim Pipeline for robotics simulation
Nana Wang,
2024/03

I use 3D Gaussain Splating to build a novel robotics simulator, the physical simulation is implemented by ISSAC SIM while the photorealistic render is implemented ny 3DGS.

3DGS implementation for ASSIST: Interactive Scene Nodes for Scalable and Realistic Indoor Simulation
Nana Wang,
2024/02

I use 3D Gaussian Splatting and nerfstudio to build a implementation, which can accomplish the 3D scene decomposition and Reconstruction.

3D Gaussian Splatting - rendering work
Nana Wang,
2023/11
code / project

I use 3D Gaussian Splatting to reconstruct some scene of Guangfulin taken by myself. Guangfulin is a beautiful park in Songjiang District, Shanghai, China.

LLM Science Exam - Use LLMs to answer difficult science questions
Nana Wang, Xiaohan Yan, Xiaowei Song
Kaggle, 2023/10
code

We gather the wiki pedia knowledge about science questions to make it into a RAG(Retrieval Augmented Generation) task, then we make three Deberta models with different finetuning and combine their output features to infer the right answer.

Pytorch-Lightning Implementation of RandLA-Net && SQN
Nana Wang
2023/10
code1 / code2

The implementation of RandLA-Net(CVPR2020) is in code0 (for large-scale semantic segmentation). and SQN(ECCV2022) is in code1 (for weak supervision schemes).

Stable Diffusion - Image to Prompts
Nana Wang, Xiaohan Yan, Xiaowei Song
Kaggle, 2023/05
code

We use a integration of ViT OFA and BLIP to make predictions on a dataset containing a wide variety of (prompt, image) pairs generated by Stable Diffusion 2.0.

Misc
Music🎶:
        I like playing the piano🎹 and have obtained certification in piano grade 10 from Shanghai Conservatory of Music.

Sports🏃‍♂️:
        I like playing basketball🏀 and I am a fun of NBA star Paul George.
        badminton🏸, swim🏊‍♂️ and etc.
Last updated on 2023/12/18