Learning cross-modal retrieval with noisy labels
Recently, cross-modal retrieval is emerging with the help of deep multimodal learning.
However, even for unimodal data, collecting large-scale well-annotated data is expensive …
However, even for unimodal data, collecting large-scale well-annotated data is expensive …
Deep supervised cross-modal retrieval
L Zhen, P Hu, X Wang, D Peng - Proceedings of the IEEE …, 2019 - openaccess.thecvf.com
Cross-modal retrieval aims to enable flexible retrieval across different modalities. The core
of cross-modal retrieval is how to measure the content similarity between different types of …
of cross-modal retrieval is how to measure the content similarity between different types of …
Integrating multi-label contrastive learning with dual adversarial graph neural networks for cross-modal retrieval
With the growing amount of multimodal data, cross-modal retrieval has attracted more and
more attention and become a hot research topic. To date, most of the existing techniques …
more attention and become a hot research topic. To date, most of the existing techniques …
Self-supervised correlation learning for cross-modal retrieval
Cross-modal retrieval aims to retrieve relevant data from another modality when given a
query of one modality. Although most existing methods that rely on the label information of …
query of one modality. Although most existing methods that rely on the label information of …
Scalable deep multimodal learning for cross-modal retrieval
P Hu, L Zhen, D Peng, P Liu - … of the 42nd international ACM SIGIR …, 2019 - dl.acm.org
Cross-modal retrieval takes one type of data as the query to retrieve relevant data of another
type. Most of existing cross-modal retrieval approaches were proposed to learn a common …
type. Most of existing cross-modal retrieval approaches were proposed to learn a common …
MHTN: Modal-adversarial hybrid transfer network for cross-modal retrieval
Cross-modal retrieval has drawn wide interest for retrieval across different modalities (such
as text, image, video, audio, and 3-D model). However, existing methods based on a deep …
as text, image, video, audio, and 3-D model). However, existing methods based on a deep …
Hcmsl: Hybrid cross-modal similarity learning for cross-modal retrieval
The purpose of cross-modal retrieval is to find the relationship between different modal
samples and to retrieve other modal samples with similar semantics by using a certain …
samples and to retrieve other modal samples with similar semantics by using a certain …
Deep multimodal transfer learning for cross-modal retrieval
Cross-modal retrieval (CMR) enables flexible retrieval experience across different
modalities (eg, texts versus images), which maximally benefits us from the abundance of …
modalities (eg, texts versus images), which maximally benefits us from the abundance of …
Cross-modal retrieval with partially mismatched pairs
P Hu, Z Huang, D Peng, X Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this paper, we study a challenging but less-touched problem in cross-modal retrieval, ie,
partially mismatched pairs (PMPs). Specifically, in real-world scenarios, a huge number of …
partially mismatched pairs (PMPs). Specifically, in real-world scenarios, a huge number of …
Modal-adversarial semantic learning network for extendable cross-modal retrieval
Cross-modal retrieval, eg, using an image query to search related text and vice-versa, has
become a highlighted research topic, to provide flexible retrieval experience across multi …
become a highlighted research topic, to provide flexible retrieval experience across multi …