Abstract Person Re-Identification (Re-ID) is a critical aspect of visual surveillance systems,
which aims to automatically recognize and locate individuals across a multi-camera network …

In the evolving landscape of surveillance and security applications, the task of person re-
identification (re-ID) has significant importance, but also presents notable difficulties. This …

In this paper, we introduce a challenging yet practical setting for person re-identification
(ReID) task, named lifelong person re-identification (LReID), which aims to continuously …

Supervised person re-identification (Re-ID) approaches are sensitive to label corrupted
data, which is inevitable and generally ignored in the field of person Re-ID. In this paper, we …

Person search aims at localizing and recognizing query persons from raw video frames,
which is a combination of two sub-tasks, ie, pedestrian detection and person re …

Image-guided depth completion (IGDC) is a multimodal computer vision task for acquiring
high-precision dense depth maps. It reasonably predicts values around accurate sparse …

Retrieving clothes which are worn in social media videos (Instagram, TikTok) is the latest
frontier of e-fashion, referred to as" video-to-shop" in the computer vision literature. In this …

Few-shot learning aims to train classifiers to learn new visual object categories from few
training examples. Recently, metric-learning based methods have made promising …

Abstract Person Re-identification (Re-ID) aims to match person images across non-
overlap** cameras. The existing approaches formulate this task as fine-grained …

Local feature extractions have been verified to be effective for person re-identification (re-ID)
in recent literature. However, existing methods usually rely on extracting local features from …