Carl Vondrick

2.6k total citations · 2 hit papers
28 papers, 1.4k citations indexed

About

Carl Vondrick is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Carl Vondrick has authored 28 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 14 papers in Artificial Intelligence and 4 papers in Control and Systems Engineering. Recurrent topics in Carl Vondrick's work include Human Pose and Action Recognition (8 papers), Multimodal Machine Learning Applications (8 papers) and Domain Adaptation and Few-Shot Learning (8 papers). Carl Vondrick is often cited by papers focused on Human Pose and Action Recognition (8 papers), Multimodal Machine Learning Applications (8 papers) and Domain Adaptation and Few-Shot Learning (8 papers). Carl Vondrick collaborates with scholars based in United States, Netherlands and United Kingdom. Carl Vondrick's co-authors include Kevin Murphy, Chen Sun, Cordelia Schmid, Austin Myers, Ruoshi Liu, Basile Van Hoorick, Pavel Tokmakov, Rundi Wu, Sergey Zakharov and Dídac Surís and has published in prestigious journals such as Scientific Reports, International Journal of Computer Vision and Science Robotics.

In The Last Decade

Carl Vondrick

27 papers receiving 1.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

VideoBERT: A Joint Model for Video and Language Representation Learning

2019 658 citations Chen Sun, Austin Myers et al. profile →
Zero-1-to-3: Zero-shot One Image to 3D Object

2023 298 citations Ruoshi Liu, Rundi Wu et al. profile →

Peers

Carl Vondrick

CVPR

AI

CGCD

CM

CSE

Aniruddha Kembhavi United States

Arun Mallya United States

Dhruv Mahajan United States

Liu Ren United States

Anyi Rao Hong Kong

Tejas D. Kulkarni United States

Lvmin Zhang Hong Kong

Mahsa Baktashmotlagh Australia

Kfir Aberman United States

Aniruddha Kembhavi United States

Carl Vondrick

1.2k ×1.3

CVPR

557 ×1.0

AI

107 ×0.7

CGCD

146 ×1.0

CM

112 ×1.1

CSE

Citations per year, relative to Carl Vondrick Carl Vondrick (= 1×) peers Aniruddha Kembhavi

Countries citing papers authored by Carl Vondrick

Since Specialization

Citations

This map shows the geographic impact of Carl Vondrick's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Carl Vondrick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carl Vondrick more than expected).

Fields of papers citing papers by Carl Vondrick

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Carl Vondrick. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Carl Vondrick. The network helps show where Carl Vondrick may publish in the future.

Co-authorship network of co-authors of Carl Vondrick

This figure shows the co-authorship network connecting the top 25 collaborators of Carl Vondrick. A scholar is included among the top collaborators of Carl Vondrick based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Carl Vondrick. Carl Vondrick is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Liu, Ruoshi, et al.. (2023). Landscape Learning for Neural Network Inversion. 29. 2239–2250. 3 indexed citations

2.

Liu, Ruoshi, Rundi Wu, Basile Van Hoorick, et al.. (2023). Zero-1-to-3: Zero-shot One Image to 3D Object. 9264–9275. 298 indexed citations breakdown →

3.

Surís, Dídac, et al.. (2023). FLEX: Full-Body Grasping Without Full-Body Grasps. 21179–21189. 17 indexed citations

4.

Creager, Elliot, et al.. (2023). SurfsUp: Learning Fluid Simulation for Novel Surfaces. 14179–14189. 1 indexed citations

5.

Mao, Chengzhi, et al.. (2023). Doubly Right Object Recognition: A Why Prompt for Visual Rationales. 2722–2732. 16 indexed citations

6.

Vondrick, Carl, et al.. (2023). Muscles in Action. 22034–22044. 6 indexed citations

7.

Surís, Dídac, Sachit Menon, & Carl Vondrick. (2023). ViperGPT: Visual Inference via Python Execution for Reasoning. 11854–11864. 87 indexed citations

8.

Hoorick, Basile Van, et al.. (2022). Revealing Occlusions with 4D Neural Fields. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 3001–3011. 7 indexed citations

9.

Surís, Dídac, Carl Vondrick, Bryan Russell, & Justin Salamon. (2022). It's Time for Artistic Correspondence in Music and Video. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 10554–10564. 22 indexed citations

10.

Vondrick, Carl, et al.. (2022). Fully body visual self-modeling of robot morphologies. Science Robotics. 7(68). eabn1944–eabn1944. 36 indexed citations

11.

Surís, Dídac, et al.. (2022). Globetrotter: Connecting Languages by Connecting Images. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 16453–16463. 5 indexed citations

12.

Chen, Boyuan, Carl Vondrick, & Hod Lipson. (2021). Visual behavior modelling for robotic theory of mind. Scientific Reports. 11(1). 424–424. 19 indexed citations

13.

Mao, Chengzhi, et al.. (2021). Adversarial Attacks are Reversible with Natural Supervision. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 641–651. 21 indexed citations

14.

Mao, Chengzhi, et al.. (2021). Generative Interventions for Causal Learning. 3946–3955. 32 indexed citations

15.

Wu, Rundi, et al.. (2020). Listening to Sounds of Silence for Speech Denoising. Neural Information Processing Systems. 33. 9633–9648. 1 indexed citations

16.

Sun, Chen, Austin Myers, Carl Vondrick, Kevin Murphy, & Cordelia Schmid. (2019). VideoBERT: A Joint Model for Video and Language Representation Learning. 7463–7472. 658 indexed citations breakdown →

17.

Pei, Kexin, Shiqi Wang, Yuchi Tian, et al.. (2019). Bringing Engineering Rigor to Deep Learning. ACM SIGOPS Operating Systems Review. 53(1). 59–67. 3 indexed citations

18.

Sellam, Thibault, et al.. (2019). DeepBase. 1117–1134. 10 indexed citations

19.

Mao, Chengzhi, Ziyuan Zhong, Junfeng Yang, Carl Vondrick, & Baishakhi Ray. (2019). Metric Learning for Adversarial Robustness. arXiv (Cornell University). 32. 478–489. 13 indexed citations

20.

Akbari, Hassan, et al.. (2019). Multi-Level Multimodal Common Semantic Space for Image-Phrase Grounding. 12468–12478. 38 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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