Selected Pulications

Publications (* equal contribution, * corresponding author. All publications on [Google Scholar])

	Learning Versatile 3D Shape Generation with Improved AR Models S. Luo, X. Qian, Y. Fu, Y. Zhang, Y. Tai, Z. Zhang, C. Wang, and X. Xue. International Conference on Computer Vision (ICCV), 2023 arXiv
	Learning Neural Proto-face Field for Disentangled 3D Face Modeling In the Wild Z. Zhang, R. Chen, W. Cao, Y. Tai, and C. Wang Computer Vision and Pattern Recognition (CVPR), 2023 Paper / Video State-of-the-art 3D portrait modeling, robust to large pose, challenging light or makeup. Also state-of-the-art novel view synthetis performance.
	RigNet: Repetitive Image Guided Network for Depth Completion Zhiqiang Yan, Kun Wang, Xiang Li, Zhenyu Zhang, Jun Li and Jian Yang European Conference on Computer Vision (ECCV), 2022 Paper
	Multi-Modal Masked Pre-Training for Monocular Panoramic Depth Completion Zhiqiang Yan, Xiang Li, Kun Wang, Zhenyu Zhang, Jun Li and Jian Yang European Conference on Computer Vision (ECCV), 2022 Paper
	Physically-Guided Disentangled Implicit Rendering for 3D Face Modeling Zhenyu Zhang, Yanhao Ge, Ying Tai, Weijian Cao, Renwang Chen, Kunlin Liu, Hao Tang, Xiaoming Huang, Chengjie Wang, Dongjin Huang, Zhifeng Xie. CVPR 2022 Paper / 3D face modeling is limited by classical graphics rendering, so that we let it benefit from a novel neural rendering approach.
	Learning to Restore 3D Face from In-the-Wild Degraded Images Zhenyu Zhang, Yanhao Ge, Ying Tai, Xiaoming Huang, Chengjie Wang, Hao Tang, Dongjin Huang, Zhifeng Xie. CVPR 2022 Paper / When restoring degraded faces, you need to restore the 3D geometry-aware effect.
	Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark Kun Wang, Zhenyu Zhang, Xiang Li, Jun Li, Baobei Xu, Jian Yang. ICCV 2021 Paper / Code Nighttime is challenging, but we make it. Dataset and code are now released.
	Learning to Aggregate and Personalize 3D Face from In-the-Wild Photo Collection Zhenyu Zhang, Yanhao Ge, Renwang Chen, Ying Tai, Yan Yan, Jian Yang, Chengjie Wang, Jinlin Li and Feiyue Huang. CVPR 2021, (Oral Presentation) Paper / Arxiv / Code Improving the non-parametric 3D face reconstruction by leveraging consistency of unconstrained photo collection.
	Cross-modal attention network for temporal inconsistent audio-visual event localization Hanyu Xuan, Zhenyu Zhang, Shuo Chen, Jian Yang, Yan Yan. AAAI 2020 Audio-visual event localization on temporal inconsistent videos
	Pattern-Structure Diffusion for Multi-Task Learning Ling Zhou, Zhen Cui, Chunyan Xu, Zhenyu Zhang, Chaoqun Wang, Tong Zhang, Jian Yang. CVPR 2020 A graph-based method to mine multi-task relationship.
	Online Depth Learning against Forgetting in Monocular Videos Zhenyu Zhang, Stephane Lathuiliere, Elisa Ricci, Nicu Sebe, Yan Yan, Jian Yang. CVPR 2020 Depth estimation method fails in new scenes, but we can continuously align it against domain shift.
	Pattern-Affinitive Propagation across Depth, Surface Normal and Semantic Segmentation Zhenyu Zhang, Zhen Cui, Chunyan Xu, Yan Yan, Nicu Sebe, Jian Yang. CVPR 2019 Feel difficult to combine different tasks? Here we provide a pair-wise similarity based method to leverage multi-task correlation.
	Joint Task-Recursive Learning for RGB-D Scene Understanding Zhenyu Zhang, Zhen Cui, Chunyan Xu, Zequn Jie, Xiang Li, Jian Yang. TPAMI 2019 A recursive approach for joint-task learning in RGBD scenes.
	Joint Task-recursive Learning for Semantic Segmentation and Depth Estimation Zhenyu Zhang, Zhen Cui, Chunyan Xu, Zequn Jie, Xiang Li, Jian Yang. ECCV 2018 A new framework for joint depth estimation & semantic segmentation.
	Progressive Hard-Mining Network for Monocular Depth Estimation Zhenyu Zhang, Chunyan Xu, Jian Yang, Junbin Gao, Zhen Cui. TIP 2018 Improving monocular depth estimation by mining difficult regions.
	Deep hierarchical guidance and regularization learning for end-to-end depth estimation Zhenyu Zhang, Chunyan Xu, Jian Yang, Ying Tai, Liang Chen. Pattern Recognition 2018 A new framework for monocular depth estimation.