World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
12658
World Ranking
7786
National Ranking
3368

Overview

Carl Vondrick is affiliated with Columbia University in the United States and specializes in Computer Science. Their research spans several subfields including Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Graphics and Computer-Aided Design, Control and Systems Engineering, and Signal Processing.

The scientist's work focuses on topics such as Multimodal Machine Learning Applications, Domain Adaptation and Few-Shot Learning, Human Pose and Action Recognition, Advanced Vision and Imaging, Advanced Image and Video Retrieval Techniques, Topic Modeling, and Computer Graphics and Visualization Techniques.

Vondrick has contributed to numerous publications predominantly in the venue arXiv (Cornell University), where they have 47 papers. Other publication venues include:

  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • elib (German Aerospace Center)
  • 2021 17th International Conference on Computational Intelligence and Security (CIS)
  • ISEE Conference Abstracts

Notable recent papers include:

  • Visual Classification via Description from Large Language Models, 2022, arXiv (Cornell University)
  • Objaverse-XL: A Universe of 10M+ 3D Objects, 2023, arXiv (Cornell University)
  • Zero-1-to-3: Zero-shot One Image to 3D Object, 2023, arXiv (Cornell University)
  • Singularity image for ClimSim-Online, 2025, elib (German Aerospace Center)
  • ViperGPT: Visual Inference via Python Execution for Reasoning, 2023, arXiv (Cornell University)

Frequent collaborators in Vondrick's research include Ruoshi Liu, Chengzhi Mao, Utkarsh Mall, Mia Chiquier, and Sachit Menon.

Best Publications

  • VideoBERT: A Joint Model for Video and Language Representation Learning

    Chen Sun;Austin Myers;Carl Vondrick;Kevin Murphy

  • Generating Videos with Scene Dynamics

    Carl Vondrick;Hamed Pirsiavash;Antonio Torralba

  • AVA: A Video Dataset of Spatio-Temporally Localized Atomic Visual Actions

    Chunhui Gu;Chen Sun;David A. Ross;Carl Vondrick

  • A large-scale benchmark dataset for event recognition in surveillance video

    Sangmin Oh;Anthony Hoogs;Amitha Perera;Naresh Cuntoor

  • SoundNet: Learning Sound Representations from Unlabeled Video

    Yusuf Aytar;Carl Vondrick;Antonio Torralba

  • Efficiently Scaling up Crowdsourced Video Annotation

    Carl Vondrick;Donald Patterson;Deva Ramanan

  • Anticipating Visual Representations from Unlabeled Video

    Carl Vondrick;Hamed Pirsiavash;Antonio Torralba

  • The Sound of Pixels

    Hang Zhao;Chuang Gan;Chuang Gan;Andrew Rouditchenko;Carl Vondrick;Carl Vondrick

  • Moments in Time Dataset: One Million Videos for Event Understanding

    Mathew Monfort;Carl Vondrick;Aude Oliva;Alex Andonian

  • Tracking Emerges by Colorizing Videos

    Carl Martin Vondrick;Abhinav Shrivastava;Alireza Fathi;Sergio Guadarrama

  • HOGgles: Visualizing Object Detection Features

    Carl Vondrick;Aditya Khosla;Tomasz Malisiewicz;Antonio Torralba

  • Do We Need More Training Data

    Xiangxin Zhu;Carl Vondrick;Charless C. Fowlkes;Deva Ramanan

  • Assessing the Quality of Actions

    Hamed Pirsiavash;Carl Vondrick;Antonio Torralba

  • Actor-Centric Relation Network

    Chen Sun;Abhinav Shrivastava;Carl Martin Vondrick;Kevin Murphy

  • Zero-1-to-3: Zero-shot One Image to 3D Object

    Unknown

  • Do We Need More Training Data or Better Models for Object Detection

    Xiangxin Zhu;Carl Vondrick;Deva Ramanan;Charless C. Fowlkes

  • Learning Aligned Cross-Modal Representations from Weakly Aligned Data

    Lluis Castrejon;Yusuf Aytar;Carl Vondrick;Hamed Pirsiavash

  • Where are they looking

    Adrià Recasens;Aditya Khosla;Carl Vondrick;Antonio Torralba

  • Generating the Future with Adversarial Transformers

    Carl Vondrick;Antonio Torralba

  • Anticipating the future by watching unlabeled video.

    Carl Vondrick;Hamed Pirsiavash;Antonio Torralba

  • AVSS 2011 demo session: A large-scale benchmark dataset for event recognition in surveillance video

    Sangmin Oh;Anthony Hoogs;Amitha Perera;Naresh Cuntoor

Frequent Co-Authors

Hamed Pirsiavash
Hamed Pirsiavash University of California, Davis
Junfeng Yang
Junfeng Yang Columbia University
Shih-Fu Chang
Shih-Fu Chang Columbia University
Deva Ramanan
Deva Ramanan Carnegie Mellon University
Chen Sun
Chen Sun Google (United States)
Abhinav Shrivastava
Abhinav Shrivastava University of Maryland, College Park
Cordelia Schmid
Cordelia Schmid French Institute for Research in Computer Science and Automation - INRIA

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Studying Computer Science in the USA can open doors to a range of jobs with elementary education and environmental science degree backgrounds, especially as technology converges with other disciplines. Hybrid skill sets are in demand, allowing candidates to qualify for diverse roles across industries.

For those interested in accelerating their education, a fast track computer science degree offers a way to enter the workforce quickly. These programs are designed for flexibility, making them ideal for working professionals or career-changers.

Exploring related STEM fields is also a smart move. Options such as an online environmental engineering degree or the cheapest mechanical engineering degree online can build strong analytical and technical skills. These degrees often share foundational coursework with computer science and offer valuable cross-disciplinary expertise.

Ultimately, expanding your knowledge through online degrees can boost your career prospects, helping you stand out in an increasingly competitive job market.

Best Scientists Citing Carl Vondrick

Trending Scientists