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Chuanxia Zheng is a Marie Skłodowska-Curie Actions (MSCA) Fellow in VGG at the University of Oxford, working with Prof. Andrea Vedaldi on feed-forward 3D reconstruction and generation. 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 Generative AI. 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. |
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His research interests focus on computer vision and machine learning, especially for creative AI. He has done a wide range of work on 2D and 3D scene synthesis, with the goal of synthesizing photorealistic physical natural world via generative AI. In particular, on topics:
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Brandon Smart, Chuanxia Zheng, Iro Laina, Victor Adrian Prisacariu arXiv, 2024 project page / arXiv / code / demo A Feed-Forward model that reconstruct 3D structure and apperance with uncalibrated images. |
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Ruining Li, Chuanxia Zheng, Christian Rupprecht, Andrea Vedaldi arXiv, 2024 project page / arXiv / code / data / demo An interactive video generative model that can serve as a motion prior for part-level dynamics. |
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Stanislaw Szymanowicz, Eldar Insafutdinov, Chuanxia Zheng, Dylan Campbell, João Henriques, Christian Rupprecht, Andrea Vedaldi, arXiv, 2024 project page / arXiv / code / demo Flash3D is a fast, super efficient, trinable on a single GPU in one day for scene 3D reconstruction from a single image. |
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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. |
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Ruining Li, Chuanxia Zheng, Christian Rupprecht, Andrea Vedaldi ECCV, 2024 project page / arXiv / code / data / demo A physical interaction with objects in vision for part-level dragging. |
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Yuedong Chen, Haofei Xu, Chuanxia Zheng, Bohan Zhuang, Marc Pollefeys, Andreas Geiger, Tat-Jen Cham, Jianfei Cai ECCV, 2024 (Oral) project page / arXiv / code A cost volume representation for efficiently predicting 3D Gaussians from sparse multi-view images in a single forward pass. |
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ClusteringSDF: Self-Organized Neural Implicit Surfaces for 3D Decomposition
Tianhao Wu, Chuanxia Zheng, Tat-Jen Cham, Qianyi Wu ECCV, 2024 project page / arXiv / code A self-organized 3D segmentation model via neural implicit surface representation. |
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Chuanxia Zheng, Andrea Vedaldi CVPR, 2024 project page / PDF / arXiv / video / code / poster Free3D synthesizes consistent novel views on open-set categories without the need of explicit 3D representations. |
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Guanqi Zhan, Chuanxia Zheng, Weidi Xie, Andrew Zisserman CVPR, 2024 project page / PDF / arXiv / code Setting up a Stable Diffusion based network to solve the amodal completion problem for any category and without occluder mask provided. |
 
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Minghui Hu, Jianbin Zheng, Chuanxia Zheng, Chaoyue Wang, Dacheng Tao, Tat-Jen Cham CVPR, 2024 project page / PDF / arXiv / code / demo A versatile plug-and-play module to fix the scheduler flaws for diffusion models. |
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Tianhao Wu, Chuanxia Zheng, Tat-Jen Cham ICLR, 2024 project page / PDF / arXiv / code An indoor panorama outpainting model using latent diffusion models with view-consistent. |
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Chuanxia Zheng, Guoxian Song, Tat-Jen Cham, Jianfei Cai, Linjie Luo, Dinh Phung T-PAMI, 2024 project page / PDF / ieeexplore / video / code PICFormer achieves pluralistic image completion with multiple and diverse solutions using a transformer based architecture at a much faster inference speed. |
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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. |
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Chuanxia Zheng, Andrea Vedaldi ICCV, 2023 project page / PDF / arXiv / video / code / poster A simple approach to avoid codebook collapse and achive 100% codebook utilisation. |
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Long Tung Vuong, Trung Le, He zhao, Chuanxia Zheng, Mehrtash Harandi, Jianfei Cai, Dinh Phung ICML, 2023 arXiv / poster / Minimize the codebook-data distortion as the Wasserstein distance. |
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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. |
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Chuanxia Zheng, Long Tung Vuong, Jianfei Cai, Dinh Phung NeurIPS, 2022 (Spotlight) project page / PDF / arXiv / video / code(Kandinsky2) / poster A spatially conditional normalization is introduced to address the repeated artifacts in vector quantized methods. |
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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. |
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Yuedong Chen, Qianyi Wu, Chuanxia Zheng, Tat-Jen Cham, Jianfei Cai, ECCV, 2022 project page / arXiv / video / code A 3D inversion model that transfers the 2D semantic map into 3D NeRF, and lets users edit 3D model through 2D semantic input. |
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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. |
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Chuanxia Zheng, Duy-Son Dao, Guoxian Song, Tat-Jen Cham, Jianfei Cai, IJCV, 2021 project page / PDF / arXiv / video / code A high-level scene understanding system that simultaneously models the completed shape and appearance for all instances. |
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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. |
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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. |
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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. |
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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. |
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Area Chair
Conference Reviewer
Journal Reviewer TPAMI, IJCV, TIP, TMM(Outstanding Reviewer Award, 2021), TCSVT, CVIU, TVCJ |
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