Feature extraction and matching are two crucial components in person Re-Identification
(ReID). The large pose deformations and the complex view variations exhibited by the …

Learning discriminative representations for unseen person images is critical for person re-
identification (ReID). Most of the current approaches learn deep representations in …

The huge variance of human pose and the misalignment of detected human images
significantly increase the difficulty of person Re-Identification (Re-ID). Moreover, efficient Re …

The huge variance of human pose and the misalign-ment of detected human images
significantly increase the difficulty of pedestrian image matching in person Re-Identification …

Person re-identification, identifying and tracking pedestrians in cross-domain monitoring
systems, is an important technology in the computer vision field and of real significance for …

The large pose variations and misalignment errors exhibited by person images significantly
increase the difficulty of person Re-Identification (ReID). Existing works commonly apply …

Recent advancements in deep learning techniques facilitate intelligent-query support in
diverse applications, such as content-based image retrieval and audio texturing. Unlike …

Person retrieval largely relies on the appearance features of pedestrians. This task is rather
more difficult in surveillance videos due to the limitations of extracting robust appearance …

Vehicle Re-Identification (Re-ID) is challenging because vehicles of the same model
commonly show similar appearance. We tackle this challenge by proposing a Global …

The manual annotation for large-scale point clouds costs a lot of time and is usually
unavailable in harsh real-world scenarios. Inspired by the great success of the pre-training …