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 …

Image-text retrieval is a fundamental task to bridge vision and language by exploiting
various strategies to fine-grained alignment between regions and words. This is still tough …

Due to the practical significance in smart video surveillance systems, Text-Based Person
Search (TBPS) has been one of the research hotspots recently, which refers to searching for …

In this paper, we present the Multi-view Extended Videos with Identities (MEVID) dataset for
large-scale, video person re-identification (ReID) in the wild. To our knowledge, MEVID …

Person search has recently been a challenging task in the computer vision domain, which
aims to search specific pedestrians from real cameras. Nevertheless, most surveillance …

Recently, Transformer-based methods have shown impressive performance in single image
super-resolution (SISR) tasks due to the ability of global feature extraction. However, the …

Weakly supervised person search aims to perform joint pedestrian detection and re-
identification (re-id) with only bounding-box annotations. Recently, the idea of contrastive …

Weakly supervised person search aims to jointly detect and match persons with only
bounding box annotations. Existing approaches typically focus on improving the features by …

Weakly supervised person search involves training a model with only bounding box
annotations, without human-annotated identities. Clustering algorithms are commonly used …

Person search is a challenging computer vision problem where the objective is to
simultaneously detect and reidentify a target person from the gallery of whole scene images …