Robust multi-view clustering with noisy correspondence
Deep multi-view clustering leverages deep neural networks to achieve promising
performance, but almost all existing methods implicitly assume that all views are aligned …
performance, but almost all existing methods implicitly assume that all views are aligned …
Noisy-correspondence learning for text-to-image person re-identification
Text-to-image person re-identification (TIReID) is a compelling topic in the cross-modal
community which aims to retrieve the target person based on a textual query. Although …
community which aims to retrieve the target person based on a textual query. Although …
Multi-memory matching for unsupervised visible-infrared person re-identification
Unsupervised visible-infrared person re-identification (USL-VI-ReID) is a promising yet
highly challenging retrieval task. The key challenges in USL-VI-ReID are to accurately …
highly challenging retrieval task. The key challenges in USL-VI-ReID are to accurately …
Robust pseudo-label learning with neighbor relation for unsupervised visible-infrared person re-identification
Unsupervised Visible-Infrared Person Re-identification (USVI-ReID) presents a formidable
challenge, which aims to match pedestrian images across visible and infrared modalities …
challenge, which aims to match pedestrian images across visible and infrared modalities …
Noise-robust Vision-language Pre-training with Positive-negative Learning
Vision-Language Pre-training (VLP) has shown promising performance in various tasks by
learning a generic image-text representation space. However, most existing VLP methods …
learning a generic image-text representation space. However, most existing VLP methods …
Learning commonality, divergence and variety for unsupervised visible-infrared person re-identification
Unsupervised visible-infrared person re-identification (USVI-ReID) aims to match specified
persons in infrared images to visible images without annotations, and vice versa. USVI-ReID …
persons in infrared images to visible images without annotations, and vice versa. USVI-ReID …
Progressive Contrastive Learning with Multi-Prototype for Unsupervised Visible-Infrared Person Re-identification
Unsupervised visible-infrared person re-identification (USVI-ReID) aims to match specified
people in infrared images to visible images without annotation, and vice versa. USVI-ReID is …
people in infrared images to visible images without annotation, and vice versa. USVI-ReID is …
Mitigate Catastrophic Remembering via Continual Knowledge Purification for Noisy Lifelong Person Re-Identification
Current Lifelong Person Re-Identification (LReID) methods focus on tackling a clean data
stream with accurate labels. When noisy data with incorrect labels are given, their …
stream with accurate labels. When noisy data with incorrect labels are given, their …
Cross-modal Retrieval with Noisy Correspondence via Consistency Refining and Mining
The success of existing cross-modal retrieval (CMR) methods heavily rely on the assumption
that the annotated cross-modal correspondence is faultless. In practice, however, the …
that the annotated cross-modal correspondence is faultless. In practice, however, the …
Adaptive Middle Modality Alignment Learning for Visible-Infrared Person Re-identification
Visible-infrared person re-identification (VIReID) has attracted increasing attention due to
the requirements for 24-hour intelligent surveillance systems. In this task, one of the major …
the requirements for 24-hour intelligent surveillance systems. In this task, one of the major …