Abstract
This paper summarizes the ChaLearn Looking at People 2020 Challenge on Identity-preserved Human Detection (IPHD). For the purpose, we released a large novel dataset containing more than 112K pairs of spatiotemporally aligned depth and thermal frames (and 175K instances of humans) sampled from 780 sequences. The sequences contain hundreds of non-identifiable people appearing in a mix of in-the-wild and scripted scenarios recorded in public and private places. The competition was divided into three tracks depending on the modalities exploited for the detection: (1) depth, (2) thermal, and (3) depth-thermal fusion. Color was also captured but only used to facilitate the groundtruth annotation. Still the temporal synchronization of three sensory devices is challenging, so bad temporal matches across modalities can occur. Hence, the labels provided should considered 'weak', although test frames were carefully selected to minimize this effect and ensure the fairest comparison of the participants' results. Despite this added difficulty, the results got by the participants demonstrate current fully-supervised methods can deal with that and achieve outstanding detection performance when measured in terms of AP@0.50.
Original language | English |
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Title of host publication | Proceedings - 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2020 |
Editors | Vitomir Struc, Francisco Gomez-Fernandez |
Number of pages | 8 |
Publisher | IEEE Signal Processing Society |
Publication date | Nov 2020 |
Pages | 801-808 |
Article number | 9320283 |
ISBN (Electronic) | 9781728130798 |
DOIs | |
Publication status | Published - Nov 2020 |
Event | 15th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2020 - Buenos Aires, Argentina Duration: 16 Nov 2020 → 20 Nov 2020 |
Conference
Conference | 15th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2020 |
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Country/Territory | Argentina |
City | Buenos Aires |
Period | 16/11/2020 → 20/11/2020 |
Sponsor | 4Paradigm, et al., Google, Universidad de Buenos Aires, Universidad de Palermo, Wrnch AI |
Series | Proceedings - 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2020 |
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Bibliographical note
Funding Information:This work was supported byTIN2015-66951-C2-2-R, RTI2018-095232-B-C22 grant from the Spanish Ministry of Science, Innovation and Universities (FEDER funds) and partially supported by the Spanish project TIN2016-74946-P (MINECO/FEDER, UE), CERCA Programme / Gener-alitat de Catalunya, and ICREA under the ICREA Academia programme. We gratefully acknowledge the support of NVIDIA Corp with the donation of the GPU used for this research.
Publisher Copyright:
© 2020 IEEE.
Keywords
- depth
- Human detection
- identity preservation
- multimodality
- privacy awareness
- thermal