Biography

Currently, I am a research fellow working and collaborating with Prof. Hanspeter Pfister & Prof. Paul Liang at Harvard University & MIT. Previously, I was a postdoctoral researcher at Max Planck Institute for Informatics with Prof. Christian Theobalt. I received my Ph.D. in Computer Science & Engineering from Nanyang Technological University, Singapore, and bachelor's degree in Communication Engineering from University of Electronic Science and Technology of China.
Coinciding with the dictum of “What I cannot create, I do not understand” by Richard Feynman, my research goals are developing & understanding intelligence emerged from the visual generation & rendering process (i.e., Generative AI). With Neural Rendering and Generative Models as general learning machine, the detailed research directions include:

  ∙ Rendering-induced intelligence, e.g., Evolutive Rendering, Neural Gauge Fields.
  ∙ Generative 3D intelligence, e.g., UNITE, IQ-VAE, SF-GAN.
  ∙ 3D for Robotics and Science, e.g., 3D-OVS

Call for papers for CVPR 2024 Workshops: Neural Rendering Intelligence and 2nd Generative Models for Computer Vision.

News

∙ [04, 2024] Invited talk at Visual Computing Group, Harvard University: Learning to Represent and Render the 3D World.
∙ [04, 2024] Invited talk at Jiajun Wu's Group, Stanford University: Towards Autonomous Scene Representation & Rendering.
∙ [04, 2024] Two papers are accepted to SIGGRAPH 2024 and TOG, respectively.
∙ [03, 2024] Invited talk at SIGS, Tsinghua University: Autonomous Rendering Intelligence.
∙ [02, 2024] Invited talk at IDS, The University of Hong Kong: Autonomous Rendering Intelligence.
∙ [12, 2023] We are organizing two workshops at CVPR 2024, including Neural Rendering Intelligence and 2nd Generative Models for Computer Vision.
∙ [09, 2023] One paper is accepted to IJCV, one is accepted to NeurIPS 2023.
∙ [08, 2023] One paper about Generative AI is accepted to TPAMI 2023.
∙ [07, 2023] Two papers are accepted to ICCV 2023.

Research Overview

Publications

Evolutive Rendering Models

Fangneng Zhan*, Hanxue Liang*, Michael Niemeyer, Yifan Wang, Michael Oechsle, Adam Kortylewski, Cengiz Oztireli, Gordon Wetzstein, Christian Theobalt
Preprint, 2024
Paper | Project
A framework for the autonomous evolution of principal elements in rendering models.

StyleGaussian: Instant 3D Style Transfer with Gaussian Splatting

Kunhao Liu, Fangneng Zhan, Muyu Xu, Christian Theobalt, Ling Shao, Shijian Lu
Preprint, 2024
Paper | Project | Code

General Neural Gauge Fields

Fangneng Zhan, Lingjie Liu, Adam Kortylewski, Christian Theobalt
International Conference on Learning Representations (ICLR), 2023
Paper | Project | Code
A general paradigm and framework for learning gauge transformations in neural fields.

TriHuman: A Real-time and Controllable Tri-plane Representation for Detailed Human Geometry and Appearance Synthesis

Heming Zhu, Fangneng Zhan, Christian Theobalt, Marc Habermann
ACM Transactions on Graphics (TOG), 2024
Paper | Project

Multimodal Image Synthesis and Editing: The Generative AI
Era

Fangneng Zhan, Yingchen Yu, Rongliang Wu, Jiahui Zhang, Shijian Lu, Lingjie Liu, Adam Kortylewski, Christian Theobalt, Eric Xing
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023 (Top50 Popular Paper)
Paper | Project | Code

DatasetNeRF: Efficient 3D-aware Data Factory with Generative Radiance Fields

Yu Chi, Fangneng Zhan, Sibo Wu, Christian Theobalt, Adam Kortylewski
The European Conference on Computer Vision (ECCV), 2024
Paper

3D Open-vocabulary Segmentation with Foundation Models

Kunhao Liu, Fangneng Zhan, Jiahui Zhang, Muyu Xu, Yingchen Yu, Abdulmotaleb El Saddik, Christian Theobalt, Eric Xing, Shijian Lu
Advances in Neural Information Processing Systems (NeurIPS), 2023
Paper | Code

WaveNeRF: Wavelet-based Generalizable Neural Radiance Fields

Muyu Xu, Fangneng Zhan, Jiahui Zhang, Yingchen Yu, Xiaoqin Zhang, Christian Theobalt, Ling Shao, Shijian Lu
IEEE International Conference on Computer Vision (ICCV), 2023
Paper | Project

A Deeper Analysis of Volumetric Relightiable Fields

Pramod Rao, Mallikarjun B R, Gereon Fox, Tim Weyrich, Bernd Bickel, Hanspeter Pfister, Wojciech Matusik, Fangneng Zhan, Ayush Tewari, Christian Theobalt, Mohamed Elgharib
International Journal of Computer Vision (IJCV), 2023 (Invited Paper)
Paper | Project

StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fields

Kunhao Liu, Fangneng Zhan, Yiwen Chen, Jiahui Zhang, Yingchen Yu, Abdulmotaleb El Saddik, Shijian Lu, Eric Xing
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)，2023
Paper | Project | Code

VMRF: View Matching Neural Radiance Fields

Jiahui Zhang, Fangneng Zhan, Rongliang Wu, Yingchen Yu, Wenqing Zhang, Song Bai, Xiaoqin Zhang, Shijian Lu
ACM International Conference on Multimedia (ACM MM), 2022
Paper

Auto-regressive Image Synthesis with Integrated Quantization

Fangneng Zhan, Yingchen Yu, Rongliang Wu, Jiahui Zhang, Kaiwen Cui, Changgong Zhang, Shijian Lu
European Conference on Computer Vision (ECCV), 2022 (Oral Presentation)
Paper | Code

Bi-level Feature Alignment for Versatile Image Translation and Manipulation

Yingchen Yu, Fangneng Zhan, Rongliang Wu, Jiahui Zhang, Kaiwen Cui, Aoran Xiao, Shijian Lu, Chunyan Miao
European Conference on Computer Vision (ECCV), 2022
Paper | Code

Marginal Correspondence for Conditional Image Generation

Fangneng Zhan, Yingchen Yu, Rongliang Wu, Jiahui Zhang, Shijian Lu, Changgong Zhang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022 (Oral Presentation)
Paper | Code | Supple

Modulated Contrast for Versatile Image Synthesis

Fangneng Zhan, Jiahui Zhang, Yingchen Yu, Rongliang Wu, Shijian Lu
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
Paper | Code | Supple

GMLight: Lighting Estimation via Geometric Distribution Approximation

Changgong Zhang, Fangneng Zhan, Yingchen Yu, Rongliang Wu, Wenbo Hu, Shijian Lu, Feiying Ma, Xuansong Xie, Ling Shao
IEEE Transactions on Image Processing (TIP), 2022
Paper | Code | Dataset | Supple

Sparse Needlets for Lighting Estimation with Spherical Transport Loss

Fangneng Zhan, Changgong Zhang, Wenbo Hu, Shijian Lu, Feiying Ma, Xuansong Xie, Ling Shao
IEEE International Conference on Computer Vision (ICCV), 2021
Paper | Code | Dataset | Supple

EMLight: Lighting Estimation via Spherical Distribution Approximation

Fangneng Zhan, Changgong Zhang, Yingchen Yu, Yuan Chang, Shijian Lu, Feiying Ma, Xuansong Xie
AAAI Conference on Artificial Intelligence (AAAI), 2021
Paper | Code | Dataset | Supple

WaveFill: A Wavelet-based Generation Network for Image Inpainting

Yingchen Yu, Fangneng Zhan, Shijian Lu, Jianxiong Pan, Feiying Ma, Xuansong Xie, Chunyan Miao
IEEE International Conference on Computer Vision (ICCV), 2021 (Oral Presentation)
Paper | Code

Unbalanced Feature Transport for Exemplar-based Image Translation

Fangneng Zhan, Yingchen Yu, Kaiwen Cui, Gongjie Zhang, Shijian Lu, Jianxiong Pan, Changgong Zhang, Feiying Ma, Xuansong Xie, Chunyan Miao
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
Paper | Project | Code | Supple

Diverse Image Inpainting with Bidirectional and Autoregressive Transformers

Yingchen Yu, Fangneng Zhan, Rongliang Wu, Jianxiong Pan, Kaiwen Cui, Shijian Lu, Feiying Ma, Xuansong Xie, Chunyan Miao
ACM International Conference on Multimedia (ACM MM), 2021 (Oral Presentation)
Paper | Code

ESIR: End-To-End Scene Text Recognition via Iterative Image Rectification

Fangneng Zhan, Shijian Lu
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Paper | Code | Supple

Verisimilar Image Synthesis for Accurate Detection and Recognition of Texts in Scenes

Fangneng Zhan, Shijian Lu, Chuhui Xue
European conference on computer vision (ECCV), 2018
Paper | Code | Dataset | Supple

Projects & Datasets

Virtual Object Relighting (VOR) Dataset for Lighting Estimation Evaluation

We create an evaluation dataset consisting of 3D scenes to conduct virtual object insertion & rendering in Blender. The lighting estimaiton performance is evaluated by using the predicted illumination map as the environment light in Blender.
Dataset | Paper | Code

Real time Scene Text Detection and Recognition System

We design a real time system for the end-to-end detection and recognition of scene texts in videos. The texts in one frame is first localized with a detection model, then a recognition model is employed to recognize the croped scene text images.
Code | Video

Academic Service

Talks:
∙ [04, 2024] Visual Computing Group, Harvard University: Learning to Represent and Render the 3D World.
∙ [04, 2024] Jiajun Wu's Group, Stanford University: Towards Autonomous Scene Representation & Rendering.
∙ [03, 2024] SIGS, Tsinghua University: Autonomous Rendering Intelligence.
∙ [02, 2024] IDS, The University of Hong Kong: Autonomous Rendering Intelligence.
∙ [03, 2023] The AI Talks: On the Gauge Transformation of Neural Fields.
Workshops & Tutorials:
∙ Organizer, CVPR 2024 Workshop: Neural Rendering Intelligence.
∙ Organizer, CVPR 2024 Workshop: 2nd Generative Models for Computer Vision.
∙ Organizer, CVPR 2023 Workshop: Generative Models for Computer Vision.
Program Committee Member:
∙ AAAI 2022, 2021, 2020
Conference & Journal Reviewer:
∙ ICML2022, ICLR 2022, NeurIPS 2021, 2020, CVPR 2022, 2021, 2020, 2019, ICCV 2021, 2019, ECCV 2020, BMVC 2021, 2020, ACCV 2020, WACV 2022, 2021
∙ TPAMI, TIP, TMM, Pattern Recognition, Neurocomputing