Humans can naturally and effectively find salient regions in complex scenes. Motivated by
this observation, attention mechanisms were introduced into computer vision with the aim of …

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 …

Attention mechanism has demonstrated great potential in fine-grained visual recognition
tasks. In this paper, we present a counterfactual attention learning method to learn more …

Person re-identification aims to retrieve persons in highly varying settings across different
cameras and scenarios, in which robust and discriminative representation learning is …

Visible-infrared person re-identification (VI-ReID) is a challenging cross-modality pedestrian
retrieval problem. Due to the large intra-class variations and cross-modality discrepancy with …

Object recognition requires a generalization capability to avoid overfitting, especially when
the samples are extremely few. Generalization from limited samples, usually studied under …

Abstract Neural Architecture Search (NAS) has been increasingly appealing to the society of
object Re-Identification (ReID), for that task-specific architectures significantly improve the …

Visible-infrared person re-identification (VI-ReID) focuses on matching the pedestrian
images of the same identity captured by different modality cameras. The part-based methods …

Object re-identification (ReID) aims to find instances with the same identity as the given
probe from a large gallery. Pairwise losses play an important role in training a strong ReID …

Few-shot class incremental learning (FSCIL) portrays the problem of learning new concepts
gradually, where only a few examples per concept are available to the learner. Due to the …