Instead, we aim to explore multiple labeled datasets to learn generalized domain-invariant representations for person re-id, which is expected universally effective for each new-coming re-id scenario.
In this paper, we propose a novel Instance-level and Spatial-Temporal Disentangled Re-ID method (InSTD), to improve Re-ID accuracy.
Ranked #12 on Person Re-Identification on DukeMTMC-reID
Given the input person image, the ensemble method would focus on the head-shoulder feature by assigning a larger weight if the individual insides the image is in black clothing.
General Instance Re-identification is a very important task in the computer vision, which can be widely used in many practical applications, such as person/vehicle re-identification, face recognition, wildlife protection, commodity tracing, and snapshop, etc.. To meet the increasing application demand for general instance re-identification, we present FastReID as a widely used software system in JD AI Research.
Ranked #1 on Person Re-Identification on MSMT17-C
The existence of this library allows developers of other DFT codes to interface with our package and achieve the charge-self-consistency within DFT+DMFT loops.
Strongly Correlated Electrons
The present study collects and evaluates these effective training tricks in person ReID.
Ranked #38 on Person Re-Identification on DukeMTMC-reID
FPR uses the error from robust reconstruction over spatial pyramid features to measure similarities between two persons.
In the literature, some effective training tricks are briefly appeared in several papers or source codes.
Ranked #2 on Person Re-Identification on UAV-Human
Video-based person re-identification (ReID) is a challenging problem, where some video tracks of people across non-overlapping cameras are available for matching.