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Computer Science

D-Index
58
Citations
19266
World Ranking
3554
National Ranking
1710

Overview

Ce Liu is a researcher affiliated with Microsoft in the United States. Their work primarily focuses on the field of Computer Science, with a specialization in Computer Vision and Pattern Recognition. Over their career, they have contributed to a broad range of subfields including Artificial Intelligence, Mechanics of Materials, Economics and Econometrics, and Computer Graphics and Computer-Aided Design.

Their research topics encompass various advanced areas such as:

  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Advanced Vision and Imaging
  • Generative Adversarial Networks and Image Synthesis
  • Advanced Image Processing Techniques
  • Advanced Neural Network Applications
  • Advanced Image and Video Retrieval Techniques

Ce Liu has an extensive publication record with a notable presence in several venues. The most frequent publication outlets include:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Interpretation
  • IEEE Transactions on Image Processing

Among their recent publications are:

  • "Florence: A New Foundation Model for Computer Vision," 2021, arXiv (Cornell University)
  • "MaskGIT: Masked Generative Image Transformer," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "GIT: A Generative Image-to-text Transformer for Vision and Language," 2022, arXiv (Cornell University)
  • "Unified Contrastive Learning in Image-Text-Label Space," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Supervised Contrastive Learning," 2020, arXiv (Cornell University)

Frequent collaborators in Ce Liu's work include:

  • Huiwen Chang
  • Lijuan Wang
  • William T. Freeman
  • Lu Yuan
  • Varun Jampani

Best Publications

  • SIFT Flow: Dense Correspondence across Scenes and Its Applications

    Ce Liu;Jenny Yuen;Antonio Torralba

  • Real-time texture synthesis by patch-based sampling

    Lin Liang;Ce Liu;Ying-Qing Xu;Baining Guo

  • Beyond pixels: exploring new representations and applications for motion analysis

    William T. Freeman;Edward H. Adelson;Ce Liu

  • Deep Convolutional Neural Network for Image Deconvolution

    Li Xu;Jimmy S Ren;Ce Liu;Jiaya Jia

  • SIFT Flow: Dense Correspondence across Different Scenes

    Ce Liu;Jenny Yuen;Antonio Torralba;Josef Sivic

  • Automatic Estimation and Removal of Noise from a Single Image

    Ce Liu;R. Szeliski;Sing Bing Kang;C.L. Zitnick

  • Supervised Contrastive Learning

    Prannay Khosla;Piotr Teterwak;Chen Wang;Aaron Sarna

  • On Bayesian Adaptive Video Super Resolution

    Ce Liu;Deqing Sun

  • Depth Transfer: Depth Extraction from Video Using Non-Parametric Sampling.

    Kevin Karsch;Ce Liu;Sing Bing Kang

  • Face Hallucination: Theory and Practice

    Ce Liu;Heung-Yeung Shum;William T. Freeman

  • Noise Estimation from a Single Image

    Ce Liu;W.T. Freeman;R. Szeliski;Sing Bing Kang

  • A two-step approach to hallucinating faces: global parametric model and local nonparametric model

    Ce Liu;Heung-Yeung Shum;Chang-Shui Zhang

  • Motion magnification

    Ce Liu;Antonio Torralba;William T. Freeman;Frédo Durand

  • Nonparametric Scene Parsing via Label Transfer

    Ce Liu;J. Yuen;A. Torralba

  • Unsupervised Joint Object Discovery and Segmentation in Internet Images

    Michael Rubinstein;Michael Rubinstein;Armand Joulin;Johannes Kopf;Ce Liu

  • Nonparametric scene parsing: Label transfer via dense scene alignment

    Ce Liu;Jenny Yuen;Antonio Torralba

  • Depth extraction from video using non-parametric sampling

    Kevin Karsch;Ce Liu;Sing Bing Kang

  • NeRD: Neural Reflectance Decomposition From Image Collections

    Mark Boss;Raphael Braun;Varun Jampani;Jonathan T. Barron

  • Florence: A New Foundation Model for Computer Vision

    Lu Yuan;Dongdong Chen;Yi-Ling Chen;Noel Codella

  • Exploring features in a Bayesian framework for material recognition

    Ce Liu;Lavanya Sharan;Edward H. Adelson;Ruth Rosenholtz

  • Depth Transfer: Depth Extraction from Videos Using Nonparametric Sampling

    Kevin Karsch;Ce Liu;Sing Bing Kang

Frequent Co-Authors

Heung-Yeung Shum
Heung-Yeung Shum Microsoft (United States)
Sing Bing Kang
Sing Bing Kang Zillow Group (United States)
Deqing Sun
Deqing Sun Google (United States)
Dilip Krishnan
Dilip Krishnan Google (United States)
Ohad Shamir
Ohad Shamir Weizmann Institute of Science
Adam Tauman Kalai
Adam Tauman Kalai Microsoft (United States)

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