Greg Shakhnarovich

3.7k total citations · 2 hit papers
19 papers, 1.6k citations indexed

About

Greg Shakhnarovich is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Developmental and Educational Psychology. According to data from OpenAlex, Greg Shakhnarovich has authored 19 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 6 papers in Human-Computer Interaction and 6 papers in Developmental and Educational Psychology. Recurrent topics in Greg Shakhnarovich's work include Advanced Vision and Imaging (8 papers), Human Pose and Action Recognition (7 papers) and Hand Gesture Recognition Systems (6 papers). Greg Shakhnarovich is often cited by papers focused on Advanced Vision and Imaging (8 papers), Human Pose and Action Recognition (7 papers) and Hand Gesture Recognition Systems (6 papers). Greg Shakhnarovich collaborates with scholars based in United States, Japan and Switzerland. Greg Shakhnarovich's co-authors include Norimichi Ukita, Muhammad Haris, Haochen Wang, Raymond A. Yeh, Jiahao Li, Karen Livescu, Bowen Shi, Diane Brentari, Adrien Gaidon and Rareş Ambruş and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Robotics and Automation Letters and Scholarworks@UNIST (Ulsan National Institute of Science and Technology).

In The Last Decade

Greg Shakhnarovich

16 papers receiving 1.6k 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.

Deep Back-Projection Networks for Super-Resolution

2018 1.1k citations Muhammad Haris, Greg Shakhnarovich et al. profile →
Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation

2023 165 citations Haochen Wang, Jiahao Li et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Greg Shakhnarovich United States	12	1.4k	733	127	119	105	19	1.6k
Anurag Ranjan Germany	10	1.2k 0.9×	174 0.2×	29 0.2×	254 2.1×	154 1.5×	21	1.5k
Baoyuan Wang China	20	1.3k 0.9×	220 0.3×	46 0.4×	103 0.9×	74 0.7×	48	1.6k
Montse Pardàs Spain	19	881 0.6×	81 0.1×	135 1.1×	39 0.3×	32 0.3×	77	1.1k
Jean‐Charles Bazin South Korea	21	1.1k 0.8×	187 0.3×	138 1.1×	226 1.9×	91 0.9×	69	1.5k
Ke Yu China	10	889 0.6×	288 0.4×	27 0.2×	27 0.2×	23 0.2×	34	1.1k
Christian Richardt United Kingdom	18	1.5k 1.1×	199 0.3×	169 1.3×	304 2.6×	477 4.5×	60	1.7k
Yuqian Zhou United States	18	1.7k 1.2×	545 0.7×	39 0.3×	51 0.4×	58 0.6×	32	1.9k
Graham Fyffe United States	18	1.4k 1.0×	170 0.2×	129 1.0×	432 3.6×	731 7.0×	41	1.6k
Huihui Bai China	18	988 0.7×	290 0.4×	10 0.1×	71 0.6×	26 0.2×	126	1.2k

Countries citing papers authored by Greg Shakhnarovich

Since Specialization

Citations

This map shows the geographic impact of Greg Shakhnarovich'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 Greg Shakhnarovich with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Greg Shakhnarovich more than expected).

Fields of papers citing papers by Greg Shakhnarovich

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Greg Shakhnarovich. 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 Greg Shakhnarovich. The network helps show where Greg Shakhnarovich may publish in the future.

Co-authorship network of co-authors of Greg Shakhnarovich

This figure shows the co-authorship network connecting the top 25 collaborators of Greg Shakhnarovich. A scholar is included among the top collaborators of Greg Shakhnarovich 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 Greg Shakhnarovich. Greg Shakhnarovich 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:

19 of 19 papers shown

Guizilini, Vitor, et al.. (2025). Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion. 764–776.

Liu, Katherine, Dian Chen, Takuya Ikeda, et al.. (2025). OmniShape: Zero-Shot Multi-Hypothesis Shape and Pose Estimation in the Real World. 16020–16027.

Shakhnarovich, Greg, et al.. (2025). SignMusketeers: An Efficient Multi-Stream Approach for Sign Language Translation at Scale. 22506–22521. 1 indexed citations

Wang, Haochen, et al.. (2024). Alpha Invariance: On Inverse Scaling Between Distance and Volume Density in Neural Radiance Fields. 20396–20405.

Wang, Haochen, et al.. (2023). Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation. 12619–12629. 165 indexed citations breakdown →

Guizilini, Vitor, et al.. (2022). Full Surround Monodepth From Multiple Cameras. IEEE Robotics and Automation Letters. 7(2). 5397–5404. 39 indexed citations

Shi, Bowen, Diane Brentari, Greg Shakhnarovich, & Karen Livescu. (2022). Searching for fingerspelled content in American Sign Language. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 1699–1712. 5 indexed citations

Guizilini, Vitor, et al.. (2022). Self-Supervised Camera Self-Calibration from Video. 2022 International Conference on Robotics and Automation (ICRA). 8468–8475. 17 indexed citations

Shi, Bowen, Diane Brentari, Greg Shakhnarovich, & Karen Livescu. (2021). Fingerspelling Detection in American Sign Language. 4164–4173. 16 indexed citations

10.

Wang, Haochen, Ruotian Luo, Michael Maire, & Greg Shakhnarovich. (2020). Pixel Consensus Voting for Panoptic Segmentation. 9461–9470. 19 indexed citations

11.

Haris, Muhammad, Greg Shakhnarovich, & Norimichi Ukita. (2020). Space-Time-Aware Multi-Resolution Video Enhancement. 2856–2865. 76 indexed citations

12.

Haris, Muhammad, Greg Shakhnarovich, & Norimichi Ukita. (2020). Deep Back-ProjectiNetworks for Single Image Super-Resolution. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(12). 4323–4337. 67 indexed citations

13.

Shi, Bowen, et al.. (2019). Fingerspelling Recognition in the Wild With Iterative Visual Attention. 5399–5408. 39 indexed citations

14.

Haris, Muhammad, Greg Shakhnarovich, & Norimichi Ukita. (2018). Deep Back-Projection Networks for Super-Resolution. 1664–1673. 1078 indexed citations breakdown →

15.

Shi, Bowen, et al.. (2018). American Sign Language Fingerspelling Recognition in the Wild. 145–152. 51 indexed citations

16.

Jiang, Huaizu, Erik Learned-Miller, Gustav Larsson, Michael Maire, & Greg Shakhnarovich. (2017). Self-Supervised Depth Learning for Urban Scene Understanding. 1 indexed citations

17.

Trivedi, Shubhendu, David McAllester, & Greg Shakhnarovich. (2014). Discriminative Metric Learning by Neighborhood Gerrymandering. Neural Information Processing Systems. 27. 3392–3400. 4 indexed citations

18.

Kim, Tae-Hwan, Greg Shakhnarovich, & Karen Livescu. (2013). Fingerspelling Recognition with Semi-Markov Conditional Random Fields. Scholarworks@UNIST (Ulsan National Institute of Science and Technology). 1521–1528. 21 indexed citations

19.

Kakade, Sham M. & Greg Shakhnarovich. (2009). Locally Weighted Regression. 15 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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