Chuanxia Zheng

Chuanxia Zheng

Chuanxia Zheng is a postdoctoral researcher in VGG at the University of Oxford, working with Prof. Andrea Vedaldi on 3D reconstruction and generation and Prof. Andrew Zisserman on generative model for understanding.

Before that, he spent one year at Monash University, where he worked as a Research Fellow with Prof. Jianfei Cai and Prof. Dinh Phung on codebook learning for generation. He received his PhD degree from the SCSE at Nanyang Technological University, supervised by Prof. Tat-Jen Cham and Prof. Jianfei Cai on 2D generation, translation and completion. His thesis Synthesizing Photorealistic Images was awarded the NTU Outstanding PhD Thesis Award 2022.

Email / CV / Google Scholar / Github / Twitter

News

2023.09: Cocktail🍸 was accepted by NeurIPS2023.
2023.07: CVQ-VAE was accepted by ICCV2023.
2023.05: I was named one of the CVPR2023 Outstanding Reviewers.
2023.04: MoVQ was reported means a lot to Kandinsky2.1., Github.
2023.04: VQ-WAE was accepted by ICML2023.
2023.01: UniD3 was accepted by ICLR2023.
2022.12: I started my research in VGG at University of Oxford.
2022.09: MoVQ was accepted by NeurIPS2022.
2022.08: Nuclear Predication was accepted by PLOS ONE.
2022.07: ObjectSDF and Semantic2NeRF were accepted by ECCV2022.
2022.06: I was the winner of the NTU Outstanding PhD Thesis Award 2022.
2022.03: Synthesizing Photorealistic Scenes was reported on media.
2022.03: TFill was accepted by CVPR2022.
2021.08: Visiting the Invisible was accepted by IJCV.
2021.07: One paper was accepted by ICCV2021.
2021.06: Pluralistic Free-Form Image Completion was accepted by IJCV.
2021.06: AgileGAN was reported by Sohu and reproduced by Open MMLab.
2021.04: AgileGAN was accepted by SIGGRAPH2021.
2021.03: FLSeSim was accepted by CVPR2021.
2019.03: Pluralistic Image Completion was accepted by CVPR2019.
2018.07: Synthetic2Real was accepted by ECCV2018.

Research

His research interests are broadly in artificial intelligence, with emphasis on computer vision and machine learning. Much of his research is about 2D image generation, completion and translation, 3D scene reconstruction, generation and completion with the goal of building intelligent machines, capable of rebuilding a photorealistic virtual world via generative AI. In particular, he is working on topics:

3D reconstruction and generation from limited views or videos.

3D editing (decomposition, recomposition, and completion) via object-centric perception.

Generative models for pyhsical world understanding.

Multi-modalities (1D, 2D, 3D, and 4D) generation and understanding.

	IPO-LDM: Depth-aided 360-degree Indoor RGB Panorama Outpainting via Latent Diffusion Model Tianhao Wu, Chuanxia Zheng, Tat-Jen Cham arXiv, 2023 project page / PDF / arXiv / code An indoor panorama outpainting model using latent diffusion models with view-consistent.
	Explicit Correspondence Matching for Generalizable Neural Radiance Fields Yuedong Chen, Haofei Xu, Qianyi Wu, Chuanxia Zheng, Tat-Jen Cham, Jianfei Cai arXiv, 2023 project page / arXiv / code Employing explicit correspondence matching as a geometry prior enables NeRF to generalize across scenes.
	Cocktail🍸: Mixing Multi-Modality Controls for Text-Conditional Image Generation Minghui Hu, Jianbin Zheng, Daqing Liu, Chuanxia Zheng, Chaoyue Wang, Dacheng Tao, Tat-Jen Cham NeurIPS, 2023 project page / PDF / arXiv / video / code We develop a generalized framework for multi-modality control based on text-to-image generation.
	Online clustered codebook Chuanxia Zheng, Andrea Vedaldi ICCV, 2023 project page / PDF / arXiv / code A simple approach to avoid codebook collapse and achive 100% codebook utilisation.
	Vector Quantized Wasserstein Auto-Encoder Long Tung Vuong, Trung Le, He zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Phung ICML, 2023 arXiv / poster / code (coming soon) Minimize the codebook-data distortion as the Wasserstein distance.
	UniD3: Unified Discrete Diffusion for Simultaneous Vision-Language Generation Minghui Hu, Chuanxia Zheng, Heliang Zheng, Tat-Jen Cham, Chaoyue Wang, Zuopeng Yang, Dacheng Tao, P.N.Suganthan, ICLR, 2023 project page / arXiv / code / A unified discrete diffusion model for simultaneous vision-language generation.
	MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generation Chuanxia Zheng, Long Tung Vuong, Jianfei Cai, Dinh Phung NeurIPS (Spotlight), 2022 project page / PDF / arXiv / video / code(Kandinsky2) / poster / A spatially conditional normalization is introduced to address the repeated artifacts in vector quantized methods.
	Object-Compositional Neural Implicit Surfaces Qianyi Wu, Xian Liu, Yuedong Chen, Kejie Li, Chuanxia Zheng, Jianfei Cai, Jianmin Zheng ECCV, 2022 project page / arXiv / video / code Automatically decompose a scene into 3D instance, trained using only 2D semantic lables and images.
	Sem2NeRF: Converting Single-View Semantic Masks to Neural Radiance Fields Yuedong Chen, Qianyi Wu, Chuanxia Zheng, Tat-Jen Cham, Jianfei Cai, ECCV, 2022 project page / arXiv / video / code We train a 3D inversion model to transfer the 2D semantic map into 3D NeRF, and lets users edit 3D model through 2D semantic input.
	Bridging global context interactions for high-fidelity image completion Chuanxia Zheng, Tat-Jen Cham, Jianfei Cai, Dinh Phung CVPR, 2022 project page / PDF / arXiv / video / code / poster TFill fills in reasonable contents for both foreground object removal and content completion.
	Visiting the Invisible: Layer-by-Layer Completed Scene Decomposition Chuanxia Zheng, Duy-Son Dao, Guoxian Song, Tat-Jen Cham, Jianfei Cai, IJCV, 2021 project page / PDF / arXiv / video / code We build a high-level scene understanding system that simultaneously models the completed shape and appearance for all instances.
	AgileGAN: Stylizing Portraits by Inversion-Consistent Transfer Learning Guoxian Song, Linjie Luo, Jing Liu, Wan-Chun Ma, Chuanxia Zheng, Tat-Jen Cham, SIGGRAPH, 2021 project page / PDF / video / code / Online Demo A GAN inversion model is trained for Stylizing Portraits.
	The Spatially-Correlative Loss for Various Image Translation Tasks Chuanxia Zheng, Tat-Jen Cham, Jianfei Cai CVPR, 2021 project page / PDF / arXiv / video / code / poster We propose a novel spatially-correlative loss that is simple, efficient and yet effective for preserving scene structure consistency while supporting large appearance changes during unpaired I2I translation.
	Pluralistic (Free-Form) Image Completion Chuanxia Zheng, Tat-Jen Cham, Jianfei Cai IJCV, 2021 CVPR, 2019 project page / PDF / arXiv / video / code / poster Given a single masked image, the proposed model is able to generate multiple and diverse plausible results.
	T2Net: Synthetic-to-Realistic Translation for Depth Estimation Tasks Chuanxia Zheng, Tat-Jen Cham, Jianfei Cai ECCV, 2018 project page / PDF / arXiv / video / code / poster Without any real depth map, the proposed model evaluates depth maps on real scenes using only synthetic datasets.

Academic Services

Conference Reviewer

CVPR	2020, 2021, 2022, 2023 (Outstanding Reviewer)
ICCV	2019, 2021, 2023
ECCV	2020, 2022
NeurIPS	2022, 2023
ICLR	2021, 2022, 2023
ICML	2023
SIGGRAPH&Asia	2022
ICRA	2022
IROS	2022
IJCAI	2022
ACM MM	2021, 2022

Journal Reviewer

TPAMI, IJCV, TIP, JAS, TMM(Outstanding Reviewer Award, 2021), TCSVT, CVIU, TVCJ, NCAA

Teaching

Teaching, Generative AI, Graduate, Oxford Summer School, 2023
Teaching Assistant, Advanced Digital Image Processing, Graduate, NTU, 2018-2020
Teaching Assistant, Human-Computer Interaction, Undergraduate, NTU, 2018-2020
Teaching Assistant, Engineering Mathematics, Undergraduate, NTU, 2018-2020

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Last updated July 2023.