Chenjie Cao

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Chenjie Cao 曹辰捷

Welcome! Chenjie Cao is at Alibaba DAMO Academy, working as a researcher of computer vision. He received his Ph.D. degree from Fudan University supervised by Prof. Yanwei Fu. His research interests focus on computer vision, which includes image inpainting, image synthesis, multi-view stereo, 3D reconstruction and generation, and feature matching.

Email / CV / Google Scholar / GitHub

Education

* Ph.D of Statistics (Machine Learning track), Fudan University, 2020 - Present.

* Master of Computer Science and Technology, East China University of Science and Technology (ECUST), 2016 - 2019.

* Bachelor of Computer Science and Technology, East China University of Science and Technology (ECUST), 2012 - 2016.

* means equal contribution

	LeftRefill: Filling Right Canvas based on Left Reference through Generalized Text-to-Image Diffusion Model. Chenjie Cao, Yunuo Cai, Qiaole Dong, Yikai Wang, Yanwei Fu CVPR 2024 page / paper / code We formulate the reference-guided multi-view synthesis as an contextual inpainting issue, which is addressed by pre-existing attention modules of pre-trained Text-to-Image model through prompt tuning.
	Repositioning the Subject within Image. Yikai Wang, Chenjie Cao, Qiaole Dong, Yifan Li, Yanwei Fu Preprint page paper / data We employ a single diffusion generative model to address various sub-tasks with task-specific prompts.
	MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View Stereo. Chenjie Cao, Xinlin Ren, Yanwei Fu ICLR 2024 paper / code We introduce MVSFormer++, a method that prudently maximizes the inherent characteristics of attention to enhance various components of the MVS pipeline.
	Towards Stable and Faithful Inpainting. Yikai Wang, Chenjie Cao, Yanwei Fu Preprint page / paper Leveraging MAE priors to stabilize the inpainting of StableDiffusion. Moreover, we propose an effective augmentation strategy to eliminate the chromatic aberration in inpainting.
	Local Consensus Enhanced Siamese Network with Reciprocal Loss for Two-view Correspondence Learning. Linbo Wang, Jing Wu, Xianyong Fang, Zhengyi Liu, Chenjie Cao, Yanwei Fu ACMMM 2023 paper A Siamese network with a reciprocal loss is proposed to classify inliers/outliers for two-view matching.
	Improving Transformer-based Image Matching by Cascaded Capturing Spatially Informative Keypoints. Chenjie Cao, Yanwei Fu ICCV 2023 page / paper / code Matching pairs located in spatially informative keypoints of both reference and target views enjoy better pose estimation. Thus a transformer-based cascaded matching model and a simple yet effective NMS filter are proposed.
	ZITS++: Image Inpainting by Improving the Incremental Transformer on Structural Priors. Chenjie Cao, Qiaole Dong, Yanwei Fu TPAMI 2023 page / paper / code The extension of CVPR work --ZITS. We further discuss the influence of various image priors on inpainting, and choice to use learning-based edges (L-Edge) as the new prior to enhance the meaningful structure recovery.
	Rethinking Optical Flow from Geometric Matching Consistent Perspective. Qiaole Dong, Chenjie Cao, Yanwei Fu CVPR 2023 page / paper / code Improving the optical flow estimation through the image matching pre-text task.
	MVSFormer: Multi-View Stereo by Learning Robust Image Features and Temperature-based Depth. Chenjie Cao, Xinlin Ren, Yanwei Fu TMLR, 2023 openreview / paper / code We explore the usage of pre-trained ViTs for multi-view stereo, and further propose to unify both classification and regression-based depth predictions. MVSFormer achieves 1-st place in Tanks-and-Temple, and achieve 2-nd place in GigaMVS2022.
	Learning Prior Feature and Attention Enhanced Image Inpainting. Chenjie Cao, Qiaole Dong, Yanwei Fu ECCV, 2022* page / paper / code Improving the image inpainting with Masked AutoEncoder pre-training and attention-based restoration.
	Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encoding. Qiaole Dong, Chenjie Cao, Yanwei Fu CVPR, 2022 page / paper / code Learning structural priors (lines, edges) with transformers at first, then recovering textures with FFC based CNNs.
	Wavelet Prior Attention Learning in Axial Inpainting Network. Chenjie Cao, Chengrong Wang, Yuntao Zhang, Yanwei Fu Preprint paper Firstly introducing wavelet prior for image inpainting. We also use axial-transformer to enhance the face/structural recovery.
	Pixel2mesh++: 3d Mesh Generation and Refinement from Multi-View Images. Chao Wen, Yinda Zhang, Chenjie Cao, Zhuwen Li, Xiangyang Xue, Yanwei Fu TPAMI, 2022 page / paper / code The extension of P2M++, which makes P2M++ also work on SDF-based methods.
	High-Fidelity Portrait Editing via Exploring Differentiable Guided Sketches from the Latent Space. Chengrong Wang, Chenjie Cao, Yanwei Fu, Xiangyang Xue ICASSP, 2022 paper Leveraging GAN inversion and differentiable edge detector to achieve an effective face editing.
	The Image Local Autoregressive Transformer. Chenjie Cao, Yuxin Hong, Xiang Li, Chengrong Wang, Chengming Xu, XiangYang Xue, Yanwei Fu NeurIPS, 2021 paper / code Propose the local autoregressive for local editing. The two-stream convolution is proposed to tackle information leakage.
	Learning a Sketch Tensor Space for Image Inpainting of Man-Made Scenes. Chenjie Cao, Yanwei Fu ICCV, 2021 page / paper / code We firstly introduce segment lines to improve the image inpainting.
	CLUE: A Chinese Language Understanding Evaluation Benchmark. Liang Xu, Xuanwei Zhang, Lu Li, Hai Hu, Chenjie Cao, Yudong Li, Yechen Xu, Kai Sun, Dian Yu, Cong Yu, Yin Tian, Qianqian Dong, Weitang Liu, Bo Shi, Yiming Cui, Junyi Li, Jun Zeng, Rongzhao Wang, Weijian Xie, Yanting Li, Yina Patterson, Zuoyu Tian, Yiwen Zhang, He Zhou, Shaoweihua Liu, Zhe Zhao, Qipeng Zhao, Cong Yue, Xinrui Zhang, Zhengliang Yang, Kyle Richardson, Zhenzhong Lan COLING, 2020 page / paper / code A comprehensive Chinese NLP benchmark.
	Entropy and Confidence-based Undersampling Boosting Random Forests for Imbalanced Problems. Zhe Wang, Chenjie Cao, Yujin Zhu TNNLS, 2020 paper My early work about using ensemble learning to address imbalanced problems.
	SiBert: Enhanced Chinese Pre-trained Language Model with Sentence Insertion. Jiahao Chen, Chenjie Cao, Xiuyan Jiang LREC, 2020 paper Improving the BERT pre-training with Sentence Insertion. SiBert won 1-st of CMRC2019.
	Cascade Interpolation Learning with Double Subspaces and Confidence Disturbance for Imbalanced Problems. Zhe Wang, Chenjie Cao NN, 2019 paper My early work about using ensemble learning to address imbalanced problems.
	IMCStacking: Cost-Sensitive Stacking Learning with Feature Inverse Mapping for Imbalanced Problems. Chenjie Cao, Zhe Wang KBS, 2018 paper My early work about using ensemble learning to address imbalanced problems.
	Information Entropy based Sample Reduction for Support Vector Data Description. Li DongDong, Zhe Wang, Chenjie Cao, Yu Liu ASC, 2018 paper My early work about using SVDD to address imbalanced problems.