Cross-modal retrieval: a systematic review of methods and future directions
With the exponential surge in diverse multi-modal data, traditional uni-modal retrieval
methods struggle to meet the needs of users demanding access to data from various …
methods struggle to meet the needs of users demanding access to data from various …
Cross-modal active complementary learning with self-refining correspondence
Recently, image-text matching has attracted more and more attention from academia and
industry, which is fundamental to understanding the latent correspondence across visual …
industry, which is fundamental to understanding the latent correspondence across visual …
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 …
Robust object re-identification with coupled noisy labels
In this paper, we reveal and study a new challenging problem faced by object Re-
IDentification (ReID), ie, Coupled Noisy Labels (CNL) which refers to the Noisy Annotation …
IDentification (ReID), ie, Coupled Noisy Labels (CNL) which refers to the Noisy Annotation …
Senet: spatial information enhancement for semantic segmentation neural networks
Y Huang, P Shi, H He, H He, B Zhao - The Visual Computer, 2024 - Springer
Image semantic segmentation is a basic task of computer vision, and plays an important role
in automatic driving, robot navigation and many other fields. However, the expensive …
in automatic driving, robot navigation and many other fields. However, the expensive …
Semantic-aware Contrastive Learning with Proposal Suppression for Video Semantic Role Grounding
Video semantic role grounding has gained substantial interest from both the academic and
industrial communities. While existing methods have demonstrated considerable …
industrial communities. While existing methods have demonstrated considerable …
Semi-supervised semi-paired cross-modal hashing
Large-scale cross-modal hashing has drawn extensive attention due to its attractive
efficiency in both storage and retrieval. Existing methods exhibit poor performance when …
efficiency in both storage and retrieval. Existing methods exhibit poor performance when …
EDMC: efficient multi-view clustering via cluster and instance space learning
Multi-view subspace clustering aims to cluster the data lying in a union of subspaces with
low dimensions. The commonly used spectral clustering performs the final clustering based …
low dimensions. The commonly used spectral clustering performs the final clustering based …
Dual-view curricular optimal transport for cross-lingual cross-modal retrieval
Current research on cross-modal retrieval is mostly English-oriented, as the availability of a
large number of English-oriented human-labeled vision-language corpora. In order to break …
large number of English-oriented human-labeled vision-language corpora. In order to break …
Fine-grained Prototypical Voting with Heterogeneous Mixup for Semi-supervised 2D-3D Cross-modal Retrieval
This paper studies the problem of semi-supervised 2D-3D retrieval which aims to align both
labeled and unlabeled 2D and 3D data into the same embedding space. The problem is …
labeled and unlabeled 2D and 3D data into the same embedding space. The problem is …