Will Price

1.9k citations
3 papers · 298 · 1 hit paper · h-index 3

Impact in

Papers in

Will Price

3 papers receiving 284 citations

Hit Papers

Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100 2021 · 188 citations
1880+1+3Years since publication50100150

Peers

Will Price
Comparison fields: 5 of 47
  • Computer Vision and Pattern Recognition 255
  • Human-Computer Interaction 23
  • Artificial Intelligence 131
  • Signal Processing 22
  • Control and Systems Engineering 23
Replace Davide Moltisanti with:
Davide Moltisanti Italy
Jonathan Munro United Kingdom
Toby Perrett United Kingdom
Michael Wray United Kingdom
Chenxia Wu China
Sandra Ebert Germany
Xijie Huang China
Atsuhiro Kojima Japan
N. Siddharth United Kingdom
Will Price relative to Davide Moltisanti Italy Davide Moltisanti's profile →
Citations per field
00.5×1.5×
Davide Moltisanti · 1×
Citations per year

Countries citing papers authored by Will Price

Since Specialization
Citations

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

Fields of papers citing papers by Will Price

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Will Price, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Will Price Line = papers co-authored together Will Price links everyone, so they are left out of the graph.

All Works

3 of 3 papers shown
#Work
1
Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100
Hit paper breakdown →
2021188
2 2020104
3 20226

About Will Price

Will Price is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Infectious Diseases, Organic Chemistry and Surgery, having authored 3 papers that have together received 298 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (3 papers), Multimodal Machine Learning Applications (3 papers), Video Analysis and Summarization (2 papers) and Domain Adaptation and Few-Shot Learning (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (255 citations), Human-Computer Interaction (23 citations), Artificial Intelligence (131 citations), Signal Processing (22 citations) and Control and Systems Engineering (23 citations). Will Price has collaborated with scholars based in United Kingdom, Italy and Netherlands. Frequent co-authors include Dima Damen, Giovanni Maria Farinella, Toby Perrett, Evangelos Kazakos, Michael Wray, Antonino Furnari, Jonathan Munro, Hazel Doughty, Davide Moltisanti and Jian Ma. Their work appears in journals such as International Journal of Computer Vision, IEEE Transactions on Pattern Analysis and Machine Intelligence and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

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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