Yin Cui

Research Scientist at Nvidia


Hi, I am Yin Cui (崔崟 in Chinese, pronounced as /yin tsui/), a research scientist at NVIDIA. Before joining Nvidia, I was a research scientist at Google. I obtained my Ph.D. in Computer Science from Cornell University and Cornell Tech in 2019, advised by Professor Serge Belongie. Together with the team, I received the PAMI Mark Everingham Prize (2023) for the COCO dataset. My research interests lie in Computer Vision and Machine Learning.

Selected Publications

  • Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception
    Hassan Akbari, Dan Kondratyuk, Yin Cui, Rachel Hornung, Huisheng Wang, Hartwig Adam
    NeurIPS 2023

  • DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model
    Xiuye Gu, Yin Cui, Jonathan Huang, Abdullah Rashwan, Xuan Yang, Xingyi Zhou, Golnaz Ghiasi, Weicheng Kuo, Huizhong Chen, Liang-Chieh Chen, David A Ross
    NeurIPS 2023

  • Module-wise Adaptive Distillation for Multimodality Foundation Models
    Chen Liang, Jiahui Yu, Ming-Hsuan Yang, Matthew Brown, Yin Cui, Tuo Zhao, Boqing Gong, Tianyi Zhou
    NeurIPS 2023

  • Unified Visual Relationship Detection with Vision and Language Models
    Long Zhao, Liangzhe Yuan, Boqing Gong, Yin Cui, Florian Schroff, Ming-Hsuan Yang, Hartwig Adam, Ting Liu
    ICCV 2023

  • A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models
    James Urquhart Allingham, Jie Ren, Michael W Dusenberry, Jeremiah Zhe Liu, Xiuye Gu, Yin Cui, Dustin Tran, Balaji Lakshminarayanan
    ICML 2023

  • F-VLM: Open-Vocabulary Object Detection upon Frozen Vision and Language Models
    Weicheng Kuo, Yin Cui, Xiuye Gu, AJ Piergiovanni, Anelia Angelova
    ICLR 2023
    [arXiv] [Website]

  • Scaling Open-Vocabulary Image Segmentation with Image-Level Labels
    Golnaz Ghiasi, Xiuye Gu, Yin Cui, Tsung-Yi Lin
    ECCV 2022
    [arXiv] [Code]

  • Open-vocabulary Object Detection via Vision and Language Knowledge Distillation
    Xiuye Gu, Tsung-Yi Lin, Weicheng Kuo, Yin Cui
    ICLR 2022
    [arXiv] [Code] [Demo]

  • Surrogate Gap Minimization Improves Sharpness-Aware Training
    Juntang Zhuang, Boqing Gong, Liangzhe Yuan, Yin Cui, Hartwig Adam, Nicha C. Dvornek, Sekhar Tatikonda, James S. Duncan, Ting Liu
    ICLR 2022
    [arXiv] [Website] [Code (in PyTorch)] [Models (in JAX)]

  • VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text
    Hassan Akbari, Liangzhe Yuan, Rui Qian, Wei-Hong Chuang, Shih-Fu Chang, Yin Cui, Boqing Gong
    NeurIPS 2021
    [arXiv] [Code]

  • Spatiotemporal Contrastive Video Representation Learning
    Rui Qian*, Tianjian Meng*, Boqing Gong, Ming-Hsuan Yang, Huisheng Wang, Serge Belongie, Yin Cui
    CVPR 2021
    [arXiv] [Code]

  • Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation
    Golnaz Ghiasi*, Yin Cui*, Aravind Srinivas*, Rui Qian, Tsung-Yi Lin, Ekin D. Cubuk, Quoc V. Le, Barret Zoph
    CVPR 2021 (Oral)
    [arXiv] [Code]

  • Rethinking Pre-training and Self-training
    Barret Zoph*, Golnaz Ghiasi*, Tsung-Yi Lin*, Yin Cui, Hanxiao Liu, Ekin D. Cubuk, Quoc V. Le
    NeurIPS 2020 (Oral)
    [arXiv] [Code]

  • Fashionpedia: Ontology, Segmentation, and an Attribute Localization Dataset
    Menglin Jia*, Mengyun Shi*, Mikhail Sirotenko*, Yin Cui*, Claire Cardie, Bharath Hariharan, Hartwig Adam, Serge Belongie
    ECCV 2020 (Oral)
    [Website] [arXiv] [Code] [Kaggle Challenge]

  • SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization
    Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Golnaz Ghiasi, Mingxing Tan, Yin Cui, Quoc V. Le, Xiaodan Song
    CVPR 2020
    [arXiv] [Code] [Google AI Blog]

  • Class-Balanced Loss Based on Effective Number of Samples
    Yin Cui, Menglin Jia, Tsung-Yi Lin, Yang Song, Serge Belongie
    CVPR 2019
    [arXiv] [Code] [Poster]

  • Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning
    Yin Cui, Yang Song, Chen Sun, Andrew Howard, Serge Belongie
    CVPR 2018
    [arXiv] [Data] [Code] [Poster] [Tensorflow Hub]

  • The iNaturalist Species Classification and Detection Dataset
    Grant Van Horn, Oisin Mac Aodha, Yang Song, Yin Cui, Chen Sun, Alex Shepard, Hartwig Adam, Pietro Perona, Serge Belongie
    CVPR 2018 (Spotlight)
    [arXiv] [Data] [Tensorflow Object Detection API] [Google AI Blog] [TechCrunch]

  • Collaborative Metric Learning
    Cheng-Kang Hsieh, Longqi Yang, Yin Cui, Tsung-Yi Lin, Serge Belongie, Deborah Estrin
    WWW 2017
    [PDF] [Code] [Slides]

  • Learning Deep Representations for Ground-to-Aerial Geolocalization
    Tsung-Yi Lin, Yin Cui, Serge Belongie, James Hays
    CVPR 2015 (Oral)
    [PDF] [Data] [Extended Abstract] [Poster]


Professional Activities

  • Area Chair of ICLR 2024, NeurIPS 2023, ICCV 2023, WACV 2023
  • Senior Program Committee (SPC) Member of AAAI 2022, AAAI 2023
  • Guest Editor of IJCV Special Issue on Open-World Visual Recognition
  • Reviewer of TPAMI, IJCV, CVPR, ICCV, ECCV, NeurIPS, ICML
  • Organizing Committee of ImageNet and COCO Visual Recognition Workshop at ICCV 2015, ECCV 2016
  • Organizing Committee of Joint Workshop of the COCO and Places Challenges at ICCV 2017
  • Organizing Committee of Joint COCO and Mapilary Recognition Challenge Workshop at ECCV 2018, ICCV 2019
  • Organizing Committee of Joint COCO and LVIS Recognition Challenge Workshop at ECCV 2020
  • Organizing Committee of Fine-Grained Visual Categorization Workshop at CVPR 2017, CVPR 2018, CVPR 2019
  • Organizing Committee of Large-scale Scene Understanding Workshop (COCO Captioning Challenge) at CVPR 2015

Selected Honors

  • PAMI Mark Everingham Prize (2023)
  • McMullen Fellowship (2014 - 2015)
  • Edwin Howard Armstrong Memorial Award (2014)
  • Wei Family Private Foundation Special Scholarship (2013)
  • National Scholarship (2010)