Learning Hierarchically Consistent Disentanglement with Multi-Channel Augmentation for Public Security-Oriented Sketch Person Re-Identification [PDF]
SensorsSketch re-identification (Re-ID) aims to retrieve pedestrian photographs in the gallery dataset by a query sketch image drawn by professionals, which is crucial for criminal investigations and missing person searches in the field of public security.
Yu Ye, Zhihong Sun, Jun Chen
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AFCLNet: An Attention and Feature-Consistency-Loss-Based Multi-Task Learning Network for Affective Matching Prediction in Music–Video Clips [PDF]
SensorsEmotion matching prediction between music and video segments is essential for intelligent mobile sensing systems, where multimodal affective cues collected from smart devices must be jointly analyzed for context-aware media understanding.
Zhibin Su +4 more
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Improvement of deep cross-modal retrieval by generating real-valued representation [PDF]
PeerJ Computer Science, 2021 The cross-modal retrieval (CMR) has attracted much attention in the research community due to flexible and comprehensive retrieval. The core challenge in CMR is the heterogeneity gap, which is generated due to different statistical properties of multi ...
Nikita Bhatt, Amit Ganatra
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Closing the Domain Gap for Cross-modal Visible-Infrared Vehicle Re-identification
2022 26th International Conference on Pattern Recognition (ICPR), 2022 Traditional vehicle re-identification (ReID) approaches, based on visible spectrum data achieve high performance, but have limited capability of real-life applications, as they perform poorly under occluded visibility conditions, such as night-time and bad weather.
Kamenou, Eleni +3 more
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Cross Task Modality Alignment Network for Sketch Face Recognition
Frontiers in Neurorobotics, 2022 The task of sketch face recognition refers to matching cross-modality facial images from sketch to photo, which is widely applied in the criminal investigation area.
Yanan Guo +5 more
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DA-GAN: Dual Attention Generative Adversarial Network for Cross-Modal Retrieval
Future Internet, 2022 Cross-modal retrieval aims to search samples of one modality via queries of other modalities, which is a hot issue in the community of multimedia. However, two main challenges, i.e., heterogeneity gap and semantic interaction across different modalities,
Liewu Cai +3 more
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Mind the Gap: Alleviating Local Imbalance for Unsupervised Cross-Modality Medical Image Segmentation
IEEE Journal of Biomedical and Health Informatics, 2023 Unsupervised cross-modality medical image adaptation aims to alleviate the severe domain gap between different imaging modalities without using the target domain label. A key in this campaign relies upon aligning the distributions of source and target domain.
Zixian Su +6 more
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Data gap decomposed by auxiliary modality for NIR‐VIS heterogeneous face recognition
IET Image Processing, 2022 In the dark scene at night, the face images captured by ordinary visible light (VIS) are generally poor quality and very dim, while the near‐infrared (NIR) can capture high definition and recognizable face images at night.
Rui Sun +3 more
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Cross‐modality person re‐identification using hybrid mutual learning
IET Computer Vision, 2023 Cross‐modality person re‐identification (Re‐ID) aims to retrieve a query identity from red, green, blue (RGB) images or infrared (IR) images. Many approaches have been proposed to reduce the distribution gap between RGB modality and IR modality. However,
Zhong Zhang +5 more
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Cross Modal Facial Image Synthesis Using a Collaborative Bidirectional Style Transfer Network
IEEE Access, 2022 In this paper, we present a novel collaborative bidirectional style transfer network based on generative adversarial network (GAN) for cross modal facial image synthesis, possibly with large modality gap.
Nizam Ud Din +4 more
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