Triplet Loss in Siamese Network for Object Tracking
By Xingping Dong, Jianbing Shen. European Conference on Computer Vision, 2018
615 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Global and Planetary Change, Safety, Risk, Reliability and Quality
View Paper: https://www.semanticscholar.org/paper/fdb98f5a7015de0956ef8d4e468257dc3079b5e5
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Maria Tzelepi
- Ali Cheraghian
- Dylan Campbell
- Lars Petersson
- Shafin Rahman
- Nikolaos Passalis
- Anastasios Tefas
- Houwen Peng
In Global and Planetary Change
- Hossein Ghanei-Yakhdan
- Seyed Mojtaba Marvasti-Zadeh
- Dylan Campbell
- Shohreh Kasaei
- Qiang Wang
- Zhipeng Zhang
- Ying Cui
- Anastasios Tefas
In Safety, Risk, Reliability and Quality
- Hossein Ghanei-Yakhdan
- Seyed Mojtaba Marvasti-Zadeh
- Dylan Campbell
- Shohreh Kasaei
- Qiang Wang
- Zhipeng Zhang
- Ying Cui
- Anastasios Tefas
Citations in the corpus
- Semantics-Enhanced Adversarial Nets for Text-to-Image Synthesis (2019, background): “In many computer vision tasks [23, 19, 4], effectively balancing easy versus hard samples is important to the training quality.”
- Transductive Zero-Shot Learning for 3D Point Cloud Classification (2019, methodology): “Learning with a Triplet Loss: Triplet losses have been widely used in computer vision [44, 32, 12, 16, 11].”
- SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking (2019, background): “Encouraged by its success, many researchers follow the work and propose some updated models [9, 35, 14, 13, 21, 20] .”
- Deep Learning for Visual Tracking: A Comprehensive Survey (2019, methodology): “ICCV 2015 HCFT [59] DAF OTB, LaSOT ICCV 2015 DeepSRDCF [60] DAF, HOG OTB, VOT2018 ECCV 2016 CCOT [64] DAF OTB, VOT2018 ECCVW 2016 SiamFC [66] DAF OTB, LaSOT CVPR 2016 SINT [67] DAF OTB, LaSOT CVPR 2016 MDNet [68] DAF OTB, LaSOT CVPR 2016 HDT [69] DAF OTB ICCV 2017, TIP 2019 PTAV [77], [78] DAF, HOG ”
- An Efficient Group Recommendation Model With Multiattention-Based Neural Networks (2020, background): “Clearly, the first four layers can compose a siamese network [46], including two branches ( C 1 –”
- Probabilistic Knowledge Transfer for Lightweight Deep Representation Learning (2020, methodology): “It is also worth noting that KT is closely related to the optimization methods [32]– [35], since it performs a relaxation of the original optimization problem, as well as to various loss functions proposed for metric learning, such as [36].”
- Deeper and Wider Siamese Networks for Real-Time Visual Tracking (2019, background): “A large amount of follow-up work [7, 12, 13, 20, 40] have been proposed, and they fall into two camps.”