A survey of approaches and trends in person re-identification

By Apurva Gala, Shishir K. Shah. 2014

471 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

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

1. Yi Yang
2. Luc Van Gool
3. Ling Shao
4. Dacheng Tao
5. Bernt Schiele
6. Xiaogang Wang
7. Ming-Hsuan Yang
8. Liang Zheng

Citations in the corpus

• Faceless Person Recognition: Privacy Implications in Social Media (2016, background): “Most previous work on person recognition in images has focused either on face images [10] (mainly frontal head) or on the surveillance scenario [11, 12], where the full body is visible, usually in low resolution.”
• Person Recognition in Personal Photo Collections (2015, background): “Data type The bulk of previous work on person recognition focus either on facial features [22] (only the head/face is visible), or on the surveillance scenario [3, 2] (full body is visible, usually in low resolution).”
• Deep Learning for Person Re-Identification: A Survey and Outlook (2020, background): “Several surveys on person Re-ID already exist, most of which are concentrated in hand-crafted systems [1], [2], [31], though some surveys have also summarized the deep learning techniques [37], [38].”
• Person Re-identification: Past, Present and Future (2016, background): “Some person re-ID surveys exist [4], [5], [6], [7].”
• Re-ranking Person Re-identification with k-Reciprocal Encoding (2017, background): “We refer the interested readers to [4, 52] for a detailed review of person re-identification (re-ID).”
• Adversarial Image Perturbation for Privacy Protection A Game Theory Perspective (2017, background): “Our case study considers the person recognition task in social media setup [5, 38, 27], as opposed to face recognition [9] (frontal faces, good lighting) or pedestrian re-identification [2, 1] (low resolution, fixed context).”
• Person Recognition in Personal Photo Collections (2017, background): “Face and surveillance re-identification is most commonly done via verification: given one reference image (gallery) and one test image (probe), do they show the same person? [4], [53].”