Towards effective person search with deep learning: A survey from systematic perspective
Person search detects and retrieves simultaneously a query person across uncropped
scene images captured by multiple non-overlapping cameras. In light of the deep learning …
scene images captured by multiple non-overlapping cameras. In light of the deep learning …
[HTML][HTML] Person search: New paradigm of person re-identification: A survey and outlook of recent works
K Islam - Image and Vision Computing, 2020 - Elsevier
Person Search (PS) has become a major field because of its need in community and in the
field of research among researchers. This task aims to find a probe person from whole scene …
field of research among researchers. This task aims to find a probe person from whole scene …
Anchor-free person search
Person search aims to simultaneously localize and identify a query person from realistic,
uncropped images, which can be regarded as the unified task of pedestrian detection and …
uncropped images, which can be regarded as the unified task of pedestrian detection and …
Self-weighted robust LDA for multiclass classification with edge classes
Linear discriminant analysis (LDA) is a popular technique to learn the most discriminative
features for multi-class classification. A vast majority of existing LDA algorithms are prone to …
features for multi-class classification. A vast majority of existing LDA algorithms are prone to …
Cascade transformers for end-to-end person search
The goal of person search is to localize a target person from a gallery set of scene images,
which is extremely challenging due to large scale variations, pose/viewpoint changes, and …
which is extremely challenging due to large scale variations, pose/viewpoint changes, and …
Updet: Universal multi-agent reinforcement learning via policy decoupling with transformers
Recent advances in multi-agent reinforcement learning have been largely limited in training
one model from scratch for every new task. The limitation is due to the restricted model …
one model from scratch for every new task. The limitation is due to the restricted model …
Sequential end-to-end network for efficient person search
Z Li, D Miao - Proceedings of the AAAI Conference on Artificial …, 2021 - ojs.aaai.org
Person search aims at jointly solving Person Detection and Person Re-identification (re-ID).
Existing works have designed end-to-end networks based on Faster R-CNN. However, due …
Existing works have designed end-to-end networks based on Faster R-CNN. However, due …
Pstr: End-to-end one-step person search with transformers
We propose a novel one-step transformer-based person search framework, PSTR, that
jointly performs person detection and re-identification (re-id) in a single architecture. PSTR …
jointly performs person detection and re-identification (re-id) in a single architecture. PSTR …
Re-id driven localization refinement for person search
Person search aims at localizing and identifying a query person from a gallery of uncropped
scene images. Different from person re-identification (re-ID), its performance also depends …
scene images. Different from person re-identification (re-ID), its performance also depends …
Tcts: A task-consistent two-stage framework for person search
The state of the art person search methods separate person search into detection and re-ID
stages, but ignore the consistency between these two stages. The general person detector …
stages, but ignore the consistency between these two stages. The general person detector …