journal article·2024Open access

Exploring Frontier Technologies in Video-Based Person Re-Identification: A Survey on Deep Learning Approach

Jiahe Wang, Xizhan Gao, Fa Zhu, Xingchi Chen

Computers, Materials & Continua· Volume 81· Issue 1

Abstract

Video-based person re-identification (Re-ID), a subset of retrieval tasks, faces challenges like uncoordinated sample capturing, viewpoint variations, occlusions, cluttered backgrounds, and sequence uncertainties. Recent adva... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Video Surveillance and Tracking Methods · Face recognition and analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (100+)

Show source-provided references
1. Person re-identification: Past, present and future
2. A survey on deep learning-based person re-identification systems10.1109/ACCESS.2019.2957336 ↗
3. Learning recurrent 3D attention for video-based person re-identification10.1109/TIP.2020.2995272 ↗
4. See the forest for the trees: Joint spatial and temporal recurrent neural networks for video-based person re-identification
5. Learning bidirectional temporal cues for video-based person re-identification10.1109/TCSVT.2017.2718188 ↗
6. Person re-identification by video ranking
7. Person re-identification by symmetry-driven accumulation of local features
8. Person reidentification using spatiotemporal appearance
9. Viewpoint invariant pedestrian recognition with an ensemble of localized features
10. Person re-identification by support vector ranking
11. Reidentification by relative distance comparison10.1109/TPAMI.2012.138 ↗
12. Domain transfer support vector ranking for person re-identification without target camera label information
13. Resource aware person re-identification across multiple resolutions
14. Deep learning for video-based person re-identification: A survey
15. Deep learning for person re-identification a survey and outlook10.1109/TPAMI.2021.3054775 ↗
16. Person re-identification based on triplet loss and improved hard positive mining in Siamese network
17. Top-push video-based person re-identification
18. A spatio-temporal appearance representation for viceo-based pedestrian re-identification
19. Person re-identification by exploiting spatio-temporal cues and multi-view metric learning10.1109/LSP.2016.2574323 ↗
20. Deep recurrent convolutional networks for video-based person re-identification: An end-to-end approach
21. Recurrent convolutional network for video-based person re-identification
22. Jointly attentive spatial-temporal pooling networks for video-based person re-identification
23. Quality aware network for set to set recognition
24. Region-based quality estimation network for large-scale person re-identification
25. Revisiting temporal modeling for video-based person ReID
26. Spatially and temporally efficient non-local attention network for video-based person re-identification
27. Global-local temporal representations for video person re-identification
28. VRSTC: Occlusion-free video person re-identification
29. Learning multi-granular hypergraphs for video-based person re-identification
30. Appearance-preserving 3D convolution for video-based person re-identification
31. Multi-granularity reference-aided attentive feature aggregation for video-based person re-identification
32. Temporal coherence or temporal motion: Which is more critical for video-based person re-identification?
33. Spatial-temporal graph convolutional network for video-based person re-identification
34. BiCnet-TKS: Learning efficient spatial-temporal representation for video person re-identification
35. Watching you: Global-guided reciprocal learning for video-based person re-identification
36. Spatio-temporal representation factorization for video-based person re-identification
37. Spatial-temporal correlation and topology learning for person re-identification in videos
38. Video-based person re-identification with spatial and temporal memory networks
39. Pyramid spatial-temporal aggregation for video-based person re-identification
40. Dense interaction learning for video-based person re-identification
41. Co-segmentation inspired attention module for video-based computer vision tasks10.1016/j.cviu.2022.103532 ↗
42. CAViT: Contextual alignment vision transformer for video object re-identification
43. Relation-based global-partial feature learning network for video-based person re-identification10.1016/j.neucom.2022.03.032 ↗
44. Video person re-identification using attribute-enhanced features10.1109/TCSVT.2022.3189027 ↗
45. A sparse graph wavelet convolution neural network for video-based person re-identification10.1016/j.patcog.2022.108708 ↗
46. Deeply coupled convolution-transformer with spatial-temporal complementary learning for video-based person re-identification
47. Feature disentanglement learning with switching and aggregation for video-based person re-identification
48. An adaptive interference removal framework for video person re-identification10.1109/TCSVT.2023.3250464 ↗
49. Where to look: Multi-granularity occlusion aware for video person re-identification10.1016/j.neucom.2023.03.003 ↗
50. Adaptive memorization with group labels for unsupervised person re-identification10.1109/TCSVT.2023.3258917 ↗
51. Spatiotemporal interaction transformer network for video-based person reidentification in internet of things10.1109/JIOT.2023.3250652 ↗
52. A video is worth three views: Trigeminal transformers for video-based person re-identification
53. TF-CLIP: Learning text-free clip for video-based person re-identification
54. Person re-identification in crowd10.1016/j.patrec.2012.02.014 ↗
55. Appearance descriptors for person re-identification: A comprehensive review
56. A survey of approaches and trends in person re-identification10.1016/j.imavis.2014.02.001 ↗
57. Survey on deep learning techniques for person re-identification task
58. Survey on person re-identification based on deep learning10.1049/trit.2018.1001 ↗
59. Deep learning-based methods for person re-identification: A comprehensive review10.1016/j.neucom.2019.01.079 ↗
60. A survey of pruning methods for efficient person re-identification across domains
61. A comprehensive overview of person re-identification approaches
62. Person search challenges and solutions: A survey
63. Unsupervised person re-identification: A systematic survey of challenges and solutions
64. A survey of open-world person re-identification10.1109/TCSVT.2019.2898940 ↗
65. Beyond part models: Person retrieval with refined part pooling
66. Non-local neural networks
67. Person re-identification with deep similarity-guided graph neural network
68. Attention is all you need
69. Ordered or orderless: A revisit for video based person re-identification10.1109/TPAMI.2020.2976969 ↗
70. Deep residual learning for image recognition
71. STA: Spatial-temporal attention for large-scale video-based person re-identification
72. Spatial and temporal mutual promotion for video-based person re-identification
73. Diversity regularized spatiotemporal attention for video-based person re-identification
74. Attribute-driven feature disentangling and temporal aggregation for video person re-identification
75. A siamese long short-term memory architecture for human re-identification
76. Preserving structural relationships for person re-identification
77. Temporal complementary learning for video person re-identification
78. Local-global associative frame assemble in video re-ID
79. Mask-guided contrastive attention model for person re-identification
80. Co-segmentation inspired attention networks for video-based person re-identification
81. Spatial-temporal attention-aware learning for video-based person re-identification10.1109/TIP.2019.2908062 ↗
82. A flow-guided mutual attention network for video-based person re-identification
83. Concentrated Multi-Grained Multi-Attention Network for Video Based Person Re-Identification
84. Multi-scale spatio-temporal feature adaptive aggregation for video-based person re-identification10.1016/j.knosys.2024.111980 ↗
85. Salient-to-broad transition for video person re-identification
86. Krizhevsky · Advances in Neural Information Processing Systems · 2012 · 25
87. Dynamic graph co-matching for unsupervised video-based person re-identification10.1109/TIP.2019.2893066 ↗
88. Person re-identification via recurrent feature aggregation
89. Deep feature learning via structured graph laplacian embedding for person re-identification10.1016/j.patcog.2018.05.007 ↗
90. Group consistent similarity learning via deep CRF for person re-identification
91. Learning context graph for person search
92. Adaptive graph representation learning for video person re-identification10.1109/TIP.2020.3001693 ↗
93. Keypoint message passing for video-based person re-identification
94. Videos as space-time region graphs
95. Multi-label image recognition with graph convolutional networks
96. Spatiotemporal transformer for video-based person re-identification
97. A duplex spatiotemporal filtering network for video-based person re-identification
98. Structured domain adaptation with online relation regularization for unsupervised person re-ID10.1109/TNNLS.2022.3173489 ↗
99. Few-shot deep adversarial learning for video-based person re-identification10.1109/TIP.2019.2940684 ↗
100. Identity preserving generative adversarial network for cross-domain person re-identification10.1109/ACCESS.2019.2933910 ↗