Stan Sclaroff

19.4k citations
213 papers · 10.6k indexed · 5 hit papers · h-index 55

Stan Sclaroff

207 papers receiving 9.9k citations

Hit Papers

Semi-Supervised Do...38719962026200620162505007501000

Peers

Stan Sclaroff
Comparison fields: 5 of 163
  • Computer Vision and Pattern Recognition 8.6k
  • Human-Computer Interaction 1.6k
  • Computer Graphics and Computer-Aided Design 303
  • Artificial Intelligence 2.3k
  • Signal Processing 777
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Citations per field
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James M. Rehg · 1×
Citations per year

Countries citing papers authored by Stan Sclaroff

Since Specialization
Citations

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

Fields of papers citing papers by Stan Sclaroff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Stan Sclaroff, 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 Stan Sclaroff Line = papers co-authored together Stan Sclaroff links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20228
2
Universal Domain Adaptation through Self Supervision
20202
3
Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation
202030
4
Are CNN Predictions based on Reasonable Evidence
20191
5 201911
6
Text-to-Clip Video Retrieval with Early Fusion and Re-Captioning.
20188
7
Differential geometric regularization for supervised learning of classifiers
20161
8 201567
9 201519
10
A Bayesian Framework for Online Classifier Ensemble
20144
11 201132
12
Benchmark Databases for Video-Based Automatic Sign Language Recognition
200866
13 20069
14
Database Indexing Methods for 3D Hand Pose Estimation
20030
15
Stochastic Refinement of the Visual Hull to Satisfy Photometric and Silhouette Consistency Constraints
200343
16 200219
17
Learning Body Pose via Specialized Maps
200168
18
Active blobs
199896
19
Visually guided animation
19961
20
Physically-based Modeling for Graphics and Vision
199310

About Stan Sclaroff

Stan Sclaroff is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Computer Graphics and Computer-Aided Design, having authored 213 papers that have together received 10.6k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (63 papers), Advanced Image and Video Retrieval Techniques (53 papers), Video Surveillance and Tracking Methods (38 papers), Advanced Vision and Imaging (38 papers), Hand Gesture Recognition Systems (30 papers), Image Retrieval and Classification Techniques (27 papers), Robotics and Sensor-Based Localization (24 papers) and Multimodal Machine Learning Applications (23 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (8.6k citations), Human-Computer Interaction (1.6k citations) and Computer Graphics and Computer-Aided Design (303 citations). Stan Sclaroff has collaborated with scholars based in United States, Italy and Mexico. Frequent co-authors include Alex Pentland, Vassilis Athitsos, Jianming Zhang, Rosalind W. Picard, Marco La Cascia, Jonathan Alon, Leonid Sigal, Zhe Lin, R. Rosales and Kate Saenko. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, Computer Vision and Image Understanding, Image and Vision Computing and IEEE Transactions on Multimedia.

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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