Ting Zhang

个人照片

I am currently a senior researcher in Visual Computing group at Microsoft Research Asia (MSRA). I obtained my B.S. (2012) and Ph.D. (2017) from University of Science and Technology of China (USTC). I had the internship at MSRA during 2012-2017 and achieved Microsoft Research Asia Fellowship award in 2015. During my PhD, I worked on approximate nearest neighbor search. After that, I joined MSRA as a permanent researcher in 2017. My work is mainly focused on computer vision, such as content generation, representation learning, large scale indexing. If you are interested in collaborating, discussing research ideas, or learning more about my work, please feel free to contact me at tinzhan@microsoft.com. [Google Scholar]

Publications and Manuscripts

Yidan Zhang, Ting Zhang, Dong Chen, Yujing Wang, Qi Chen, Xing Xie, Hao Sun, Weiwei Deng, Qi Zhang, Fan Yang, et al. “IRGen: Generative Modeling for Image Retrieval”. In: arXiv preprint arXiv:2303.10126 (2023). [pdf]
Junshu Tang, Tengfei Wang, Bo Zhang, Ting Zhang, Ran Yi, Lizhuang Ma, and Dong Chen. “Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior”. In: arXiv preprint arXiv:2303.14184 (2023). [pdf] [code]
Tengfei Wang, Bo Zhang, Ting Zhang, Shuyang Gu, Jianmin Bao, Tadas Baltrusaitis, Jingjing Shen, Dong Chen, Fang Wen, Qifeng Chen, et al. “Rodin: A Generative Model for Sculpting 3D Digital Avatars Using Diffusion”. In: arXiv preprint arXiv:2212.06135 (2022). [pdf]
Binxin Yang, Shuyang Gu, Bo Zhang, Ting Zhang, Xuejin Chen, Xiaoyan Sun, Dong Chen, and Fang Wen. “Paint by Example: Exemplar-based Image Editing with Diffusion Models”. In: arXiv preprint arXiv:2211.13227 (2022). [pdf] [code]
Xiaoyi Dong, Jianmin Bao, Ting Zhang, Dongdong Chen, Shuyang Gu, Weiming Zhang, Lu Yuan, Dong Chen, Fang Wen, and Nenghai Yu. “CLIP Itself is a Strong Fine-tuner: Achieving 85.7% and 88.0% Top-1 Accuracy with ViT-B and ViT-L on ImageNet”. In: arXiv preprint arXiv:2212.06138 (2022). [pdf] [code]
Xiaoyi Dong, Yinglin Zheng, Jianmin Bao, Ting Zhang, Dongdong Chen, Hao Yang, Ming Zeng, Weiming Zhang, Lu Yuan, Dong Chen, et al. “Maskclip: Masked self-distillation advances contrastive language-image pretraining”. In: arXiv preprint arXiv:2208.12262 (2022). [pdf]
Junshu Tang, Bo Zhang, Binxin Yang, Ting Zhang, Dong Chen, Lizhuang Ma, and Fang Wen. “Explicitly controllable 3d-aware portrait generation”. In: arXiv preprint arXiv:2209.05434 (2022). [pdf] [code]
Tengfei Wang, Ting Zhang, Bo Zhang, Hao Ouyang, Dong Chen, Qifeng Chen, and Fang Wen. “Pretraining is all you need for image-to-image translation”. In: arXiv preprint arXiv:2205.12952 (2022). [pdf] [code]
Yinglin Zheng, Hao Yang, Ting Zhang, Jianmin Bao, Dongdong Chen, Yangyu Huang, Lu Yuan, Dong Chen, Ming Zeng, and Fang Wen. “General facial representation learning in a visual- linguistic manner”. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2022, pp. 18697–18709. [pdf] [code]
Xiaoyi Dong, Jianmin Bao, Ting Zhang, Dongdong Chen, Weiming Zhang, Lu Yuan, Dong Chen, Fang Wen, and Nenghai Yu. “Bootstrapped Masked Autoencoders for Vision BERT Pretraining”. In: Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXX. Springer. 2022, pp. 247–264. [pdf] [code]
Xiaoyi Dong, Jianmin Bao, Dongdong Chen, Ting Zhang, Weiming Zhang, Nenghai Yu, Dong Chen, Fang Wen, and Baining Guo. “Protecting celebrities from deepfake with identity con- sistency transformer”. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2022, pp. 9468–9478. [pdf] [code]
Xingran Zhou, Bo Zhang, Ting Zhang, Pan Zhang, Jianmin Bao, Dong Chen, Zhongfei Zhang, and Fang Wen. “Cocosnet v2: Full-resolution correspondence learning for image translation”. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021, pp. 11465–11475. [pdf] [code]
Xiaoyi Dong, Jianmin Bao, Ting Zhang, Dongdong Chen, Weiming Zhang, Lu Yuan, Dong Chen, Fang Wen, and Nenghai Yu Peco. “Perceptual codebook for bert pre-training of vision transformers”. In: arXiv preprint arXiv:2111.12710 2.6 (2021). [pdf]
Pan Zhang, Bo Zhang, Ting Zhang, Dong Chen, Yong Wang, and Fang Wen. “Prototypical pseudo label denoising and target structure learning for domain adaptive semantic segmentation”. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2021, pp. 12414–12424. [pdf] [code]
Lingzhi Li, Jianmin Bao, Ting Zhang, Hao Yang, Dong Chen, Fang Wen, and Baining Guo. “Face x-ray for more general face forgery detection”. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2020, pp. 5001–5010. [pdf]
Xiang Ming, Fangyun Wei, Ting Zhang, Dong Chen, Nanning Zheng, and Fang Wen. “Group Sampling for Scale Invariant Face Detection”. In: IEEE Transactions on Pattern Analysis & Machine Intelligence 44.02 (2020), pp. 985–1001. [pdf]
Pan Zhang, Bo Zhang, Ting Zhang, Dong Chen, and Fang Wen. “Robust mutual learning for semi-supervised semantic segmentation”. In: arXiv preprint arXiv:2106.00609 (2021). [pdf]
Guotian Xie, Kuiyuan Yang, Ting Zhang, Jingdong Wang, and Jianhuang Lai. “Balanced de- coupled spatial convolution for CNNs”. In: IEEE transactions on neural networks and learning systems 30.11 (2019), pp. 3419–3432. [pdf]
Pan Zhang, Jianmin Bao, Ting Zhang, Dong Chen, and Fang Wen. “Semi-Supervised Image- to-Image Translation using Latent Space Mapping”. In: arXiv preprint arXiv:2203.15241 (2022). [pdf]
Xiang Ming, Fangyun Wei, Ting Zhang, Dong Chen, and Fang Wen. “Group sampling for scale invariant face detection”. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019, pp. 3446–3456. [pdf]
Guotian Xie, Jingdong Wang, Ting Zhang, Jianhuang Lai, Richang Hong, and Guo-Jun Qi. “Interleaved structured sparse convolutional neural networks”. In: Proceedings of the IEEE Con- ference on Computer Vision and Pattern Recognition. 2018, pp. 8847–8856. [pdf]
Guotian Xie, Ting Zhang, Kuiyuan Yang, Jianhuang Lai, and Jingdong Wang. “Decoupled convolutions for cnns”. In: Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 32. 1. 2018. [pdf]
Jingdong Wang and Ting Zhang. “Composite quantization”. In: IEEE transactions on pattern analysis and machine intelligence 41.6 (2018), pp. 1308–1322. [pdf]
Ting Zhang, Guo-Jun Qi, Bin Xiao, and Jingdong Wang. “Interleaved group convolutions”. In: Proceedings of the IEEE international conference on computer vision. 2017, pp. 4373–4382. [pdf] [code]
Jingdong Wang, Ting Zhang, Jingkuan Song, Nicu Sebe, and Heng Tao Shen. “A survey on learning to hash”. In: IEEE transactions on pattern analysis and machine intelligence 40.4 (2017), pp. 769–790. [pdf]
Xiaojuan Wang, Ting Zhang, Guo-Jun Qi, Jinhui Tang, and Jingdong Wang. “Supervised quan- tization for similarity search”. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016, pp. 2018–2026. [pdf]
Jingdong Wang, Zhen Wei, Ting Zhang, and Wenjun Zeng. “Deeply-fused nets”. In: arXiv preprint arXiv:1605.07716 (2016). [pdf]
Ting Zhang and Jingdong Wang. “Collaborative quantization for cross-modal similarity search”. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016, pp. 2036–2045. [pdf]
Ting Zhang, Guo-Jun Qi, Jinhui Tang, and Jingdong Wang. “Sparse composite quantization”. In: Proceedings of the IEEE conference on computer vision and pattern recognition. 2015, pp. 4548– 4556. [pdf]
Ting Zhang, Chao Du, and Jingdong Wang. “Composite quantization for approximate nearest neighbor search”. In: International Conference on Machine Learning. PMLR. 2014, pp. 838–846. [pdf] [code]

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