Manolis Savva

17.9k total citations · 2 hit papers
49 papers, 5.1k citations indexed

About

Manolis Savva is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Geology. According to data from OpenAlex, Manolis Savva has authored 49 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Computer Vision and Pattern Recognition, 19 papers in Computational Mechanics and 12 papers in Geology. Recurrent topics in Manolis Savva's work include 3D Shape Modeling and Analysis (19 papers), Advanced Vision and Imaging (15 papers) and 3D Surveying and Cultural Heritage (12 papers). Manolis Savva is often cited by papers focused on 3D Shape Modeling and Analysis (19 papers), Advanced Vision and Imaging (15 papers) and 3D Surveying and Cultural Heritage (12 papers). Manolis Savva collaborates with scholars based in United States, Canada and China. Manolis Savva's co-authors include Anne Lynn S. Chang, Thomas Funkhouser, Angela Dai, Maciej Halber, Matthias Nießner, Pat Hanrahan, Matthew Fisher, Shuran Song, Matthias NieBner and Yinda Zhang and has published in prestigious journals such as ACM Transactions on Graphics, Computer Graphics Forum and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

In The Last Decade

Manolis Savva

46 papers receiving 5.0k 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.

ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes

2017 2.3k citations Angela Dai, Anne Lynn S. Chang et al. profile →
Matterport3D: Learning from RGB-D Data in Indoor Environments

2017 950 citations Anne Lynn S. Chang, Angela Dai et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Manolis Savva United States	21	3.7k	1.7k	1.4k	1.3k	795	49	5.1k
Angela Dai Germany	20	3.7k 1.0×	1.9k 1.1×	1.8k 1.3×	1.9k 1.4×	904 1.1×	48	5.2k
Jaesik Park South Korea	22	3.2k 0.9×	896 0.5×	968 0.7×	1.1k 0.9×	540 0.7×	58	4.3k
Yinda Zhang United States	25	2.3k 0.6×	748 0.5×	362 0.3×	575 0.4×	608 0.8×	55	3.0k
Andy Zeng United States	18	1.9k 0.5×	558 0.3×	631 0.5×	1.0k 0.8×	166 0.2×	28	3.4k
Philip Lenz Germany	4	4.4k 1.2×	386 0.2×	726 0.5×	2.3k 1.8×	168 0.2×	5	5.9k
Yongming Rao China	29	2.4k 0.6×	828 0.5×	556 0.4×	229 0.2×	346 0.4×	49	3.4k
Andrei Sharf Israel	29	1.4k 0.4×	1.3k 0.8×	988 0.7×	413 0.3×	995 1.3×	71	2.9k
Ralph R. Martin United Kingdom	28	1.4k 0.4×	1.3k 0.8×	494 0.4×	306 0.2×	791 1.0×	98	3.0k
Sudipta N. Sinha United States	29	3.0k 0.8×	168 0.1×	680 0.5×	1.6k 1.3×	347 0.4×	60	3.9k
Sven Dickinson Canada	30	3.4k 0.9×	783 0.5×	206 0.1×	689 0.5×	303 0.4×	103	4.2k

Countries citing papers authored by Manolis Savva

Since Specialization

Citations

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

Fields of papers citing papers by Manolis Savva

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manolis Savva

This figure shows the co-authorship network connecting the top 25 collaborators of Manolis Savva. A scholar is included among the top collaborators of Manolis Savva 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 Manolis Savva. Manolis Savva 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.

Chang, Anne Lynn S., et al.. (2025). SceneMotifCoder: Example-Driven Visual Program Learning for Generating 3D Object Arrangements. 179–188.

2.

Lee, Heeyoung, Manolis Savva, & Anne Lynn S. Chang. (2024). Text‐to‐3D Shape Generation. Computer Graphics Forum. 43(2). 4 indexed citations

3.

Liu, Jiayi, et al.. (2024). CAGE: Controllable Articulation GEneration. 17880–17889. 9 indexed citations

4.

Wu, Qirui, Daniel Ritchie, Manolis Savva, & Anne Lynn S. Chang. (2024). Generalizing Single-View 3D Shape Retrieval to Occlusions and Unseen Objects. 893–902.

5.

Jiang, Hanxiao, Dhruv Batra, Alexander Clegg, et al.. (2024). Habitat Synthetic Scenes Dataset (HSSD-200): An Analysis of 3D Scene Scale and Realism Tradeoffs for ObjectGoal Navigation. 16384–16393. 13 indexed citations

6.

Mahdavian, Mohammad, et al.. (2024). DMFuser: Distilled Multi-Task Learning for End-to-end Transformer-Based Sensor Fusion in Autonomous Driving. 14188–14195.

7.

Li, Manyi, et al.. (2023). Advances in Data‐Driven Analysis and Synthesis of 3D Indoor Scenes. Computer Graphics Forum. 43(1). 7 indexed citations

8.

Chang, Anne Lynn S., et al.. (2023). Evaluating 3D Shape Analysis Methods for Robustness to Rotation Invariance. 257. 63–72. 1 indexed citations

9.

Jiang, Hanxiao, et al.. (2022). Articulated 3D Human-Object Interactions From RGB Videos: An Empirical Analysis of Approaches and Challenges. 312–321. 7 indexed citations

10.

Jain, Unnat, et al.. (2021). Interpretation of Emergent Communication in Heterogeneous Collaborative Embodied Agents. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 15953–15963. 1 indexed citations

11.

Tan, Jiaqi, et al.. (2021). Mirror3D: Depth Refinement for Mirror Surfaces. 15985–15994. 24 indexed citations

12.

Li, Manyi, et al.. (2021). LayoutGMN: Neural Graph Matching for Structural Layout Similarity. 11043–11052. 14 indexed citations

13.

Chen, Changan, et al.. (2020). Relational Graph Learning for Crowd Navigation. 10007–10013. 97 indexed citations

14.

Wijmans, Erik, Abhishek Kadian, Ari S. Morcos, et al.. (2019). Decentralized Distributed PPO: Solving PointGoal Navigation. arXiv (Cornell University). 8 indexed citations

15.

Dai, Angela, Anne Lynn S. Chang, Manolis Savva, et al.. (2017). ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes. 2432–2443. 2255 indexed citations breakdown →

16.

Savva, Manolis, Anne Lynn S. Chang, Pat Hanrahan, Matthew Fisher, & Matthias Nießner. (2016). PiGraphs. ACM Transactions on Graphics. 35(4). 1–12. 80 indexed citations

17.

Hu, Ruizhen, Oliver van Kaick, Youyi Zheng, & Manolis Savva. (2016). SIGGRAPH Asia 2016. 1–326. 1 indexed citations

18.

Chang, Anne Lynn S., Manolis Savva, & Christopher D. Manning. (2014). Learning Spatial Knowledge for Text to 3D Scene Generation. 2028–2038. 93 indexed citations

19.

Chang, Anne Lynn S., Manolis Savva, & Christopher D. Manning. (2014). Interactive Learning of Spatial Knowledge for Text to 3D Scene Generation. 14–21. 15 indexed citations

20.

Kairam, Sanjay, Diana MacLean, Manolis Savva, & Jeffrey Heer. (2012). GraphPrism. 498–505. 31 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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