The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
A Unified Framework for Multi-target Tracking and Collective Activity Recognition
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Histograms of Oriented Gradients for Human Detection
Dalal, N., & Triggs, B. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.177 · Cited by 33,584
You'll never walk alone: Modeling social behavior for multi-target tracking
Pellegrini, S., Ess, A., Schindler, K., & van Gool, L. (2009) · 2009 IEEE 12th International Conference on Computer Vision · doi:10.1109/iccv.2009.5459260 · Cited by 1,683 · cited 2×
“Much of the existing literature on activity recognition and tracking [3–11] avoids the complexity of this context-rich approach by seeking to solve the problems in isolation.”
BackgroundGlobally-optimal greedy algorithms for tracking a variable number of objects
Pirsiavash, H., Ramanan, D., & Fowlkes, C. C. (2011) · CVPR 2011 · doi:10.1109/cvpr.2011.5995604 · Cited by 790
A mobile vision system for robust multi-person tracking
Ess, A., Leibe, B., Schindler, K., & Van Gool, L. (2008) · 2008 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2008.4587581 · Cited by 721
Learning pedestrian dynamics from the real world
Scovanner, P., & Tappen, M. F. (2009) · 2009 IEEE 12th International Conference on Computer Vision · doi:10.1109/iccv.2009.5459224 · Cited by 135
Cited by
Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks
Gupta, A., Johnson, J., Fei-Fei, L., Savarese, S., & Alahi, A. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00240 · Cited by 2,466
Self-citationLearning Social Etiquette: Human Trajectory Understanding In Crowded Scenes
Robicquet, A., Sadeghian, A., Alahi, A., & Savarese, S. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46484-8_33 · Cited by 927
Self-citationLearning a Neural Solver for Multiple Object Tracking
Braso, G., & Leal-Taixe, L. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00628 · Cited by 504
Multi-Agent Tensor Fusion for Contextual Trajectory Prediction
Zhao, T., Xu, Y., Monfort, M., Choi, W., Baker, C., Zhao, Y., Wang, Y., & Wu, Y. N. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.01240 · Cited by 477
Self-citationLearning by Tracking: Siamese CNN for Robust Target Association
Leal-Taixe, L., Canton-Ferrer, C., & Schindler, K. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2016.59 · Cited by 444
Metadata
- Authors
- Choi, W., & Savarese, S.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2012
- Pages
- 215-230
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W100367037
- Cited by
- 351
- References
- 5
- FWCI
- 16.18
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A Unified Framework for Multi-target Tracking and Collective Activity Recognition. https://app.cochat.ai/papers/10.1007/978-3-642-33765-9_16
- The paper
- Choi, W., & Savarese, S. (2012). A Unified Framework for Multi-target Tracking and Collective Activity Recognition. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-642-33765-9_16
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
