Person Re-Identification
원문 초록
Person Re-Identification (Re-ID) is an important problem in computer vision-based surveillance applications, in which one aims to identify a person across different surveillance photographs taken from different cameras having varying orientations and field of views. Due to the increasing demand for intelligent video surveillance, Re-ID has gained significant interest in the computer vision community. In this work, we experiment on some existing Re-ID methods that obtain state of the art performance in some open benchmarks. We qualitatively and quantitaively analyse their performance on a provided dataset, and then propose methods to improve the results. This work was the report submitted for COL780 final project at IIT Delhi.
함께 살펴볼 논문
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Try Harder: Hard Sample Generation and Learning for Clothes-Changing Person Re-ID
Following the Clues: Experiments on Person Re-ID using Cross-Modal Intelligence
Domain Generalization for Person Re-identification: A Survey Towards Domain-Agnostic Person Matching
ReID5o: Achieving Omni Multi-modal Person Re-identification in a Single Model
S3CE-Net: Spike-guided Spatiotemporal Semantic Coupling and Expansion Network for Long Sequence Event Re-Identification
Differentiable Channel Selection in Self-Attention For Person Re-Identification
토론
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