Daniel Erickson

520 total citations
9 papers, 350 citations indexed

About

Daniel Erickson is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Artificial Intelligence. According to data from OpenAlex, Daniel Erickson has authored 9 papers receiving a total of 350 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 6 papers in Computer Graphics and Computer-Aided Design and 2 papers in Artificial Intelligence. Recurrent topics in Daniel Erickson's work include Computer Graphics and Visualization Techniques (6 papers), Advanced Vision and Imaging (6 papers) and Image and Signal Denoising Methods (2 papers). Daniel Erickson is often cited by papers focused on Computer Graphics and Visualization Techniques (6 papers), Advanced Vision and Imaging (6 papers) and Image and Signal Denoising Methods (2 papers). Daniel Erickson collaborates with scholars based in United States. Daniel Erickson's co-authors include Ryan Overbeck, Paul Debevec, Matt Pharr, John P. Flynn, Matt Whalen, Michael Broxton, Jay Busch, Jason Dourgarian, Matthew DuVall and Peter Hedman and has published in prestigious journals such as ACM Transactions on Graphics and MPG.PuRe (Max Planck Society).

In The Last Decade

Daniel Erickson

8 papers receiving 334 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel Erickson United States	7	323	175	56	37	28	9	350
Jason Dourgarian United States	4	246 0.8×	115 0.7×	37 0.7×	31 0.8×	20 0.7×	5	280
Janne Kontkanen United States	9	333 1.0×	214 1.2×	84 1.5×	50 1.4×	17 0.6×	16	387
Matthew DuVall United States	5	397 1.2×	252 1.4×	91 1.6×	38 1.0×	25 0.9×	6	429
John Isidoro United States	9	471 1.5×	136 0.8×	87 1.6×	104 2.8×	24 0.9×	17	519
YiChang Shih United States	9	613 1.9×	125 0.7×	40 0.7×	137 3.7×	11 0.4×	13	663
T. Takai Japan	6	249 0.8×	95 0.5×	56 1.0×	18 0.5×	23 0.8×	10	269
Jiamin Bai United States	10	324 1.0×	87 0.5×	20 0.4×	49 1.3×	66 2.4×	15	361
Anita Sellent Germany	8	229 0.7×	92 0.5×	35 0.6×	62 1.7×	9 0.3×	19	247
Abhimitra Meka United States	9	278 0.9×	165 0.9×	99 1.8×	37 1.0×	6 0.2×	13	352
Ang Cao United States	5	213 0.7×	130 0.7×	82 1.5×	6 0.2×	14 0.5×	11	273

Countries citing papers authored by Daniel Erickson

Since Specialization

Citations

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

Fields of papers citing papers by Daniel Erickson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Erickson

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

9 of 9 papers shown

1.

Meka, Abhimitra, Rohit Pandey, Christian Häne, et al.. (2020). Deep Relightable Textures Volumetric Performance Capture with Neural Rendering. MPG.PuRe (Max Planck Society). 36 indexed citations

2.

Broxton, Michael, John P. Flynn, Ryan Overbeck, et al.. (2020). Immersive light field video with a layered mesh representation. ACM Transactions on Graphics. 39(4). 173 indexed citations

3.

Broxton, Michael, Jay Busch, Jason Dourgarian, et al.. (2020). DeepView Immersive Light Field Video. 1–2. 9 indexed citations

4.

Broxton, Michael, Jay Busch, Jason Dourgarian, et al.. (2019). A Low Cost Multi-Camera Array for Panoramic Light Field Video Capture. 1–2. 7 indexed citations

5.

Overbeck, Ryan, et al.. (2018). A system for acquiring, processing, and rendering panoramic light field stills for virtual reality. ACM Transactions on Graphics. 37(6). 1–15. 106 indexed citations

6.

Overbeck, Ryan, et al.. (2018). The making of welcome to light fields VR. 1–2. 8 indexed citations

7.

Overbeck, Ryan, et al.. (2018). Welcome to light fields. 1–1. 10 indexed citations

8.

Erickson, Daniel, et al.. (2003). A neural network approach to image compression. 6. 2921–2924. 1 indexed citations

9.

Erickson, Daniel, et al.. (2002). Variable rate self organizing neural networks for video compression. 1. 244–248.

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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