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Found 7 papers, 1 papers with code
Salient Object Detection From Arbitrary Modalities
The most prominent characteristics of AM SOD are that the modality types and modality numbers will be arbitrary or dynamically changed.
Modality Prompts for Arbitrary Modality Salient Object Detection
A novel modality-adaptive Transformer (MAT) will be proposed to investigate two fundamental challenges of AM SOD, ie more diverse modality discrepancies caused by varying modality types that need to be processed, and dynamic fusion design caused by an uncertain number of modalities present in the inputs of multimodal fusion strategy.
On Exploring Pose Estimation as an Auxiliary Learning Task for Visible-Infrared Person Re-identification
Visible-infrared person re-identification (VI-ReID) has been challenging due to the existence of large discrepancies between visible and infrared modalities.
FMCNet: Feature-Level Modality Compensation for Visible-Infrared Person Re-Identification
Then, a feature-level modality compensation module is present to generate those missing modality-specific features from existing modality-shared ones.
ABMDRNet: Adaptive-Weighted Bi-Directional Modality Difference Reduction Network for RGB-T Semantic Segmentation
Semantic segmentation models gain robustness against poor lighting conditions by virtue of complementary information from visible (RGB) and thermal images.
Ranked #27 on
Thermal Image Segmentation
on MFN Dataset
Middle-level Fusion for Lightweight RGB-D Salient Object Detection
The former one first uses two sub-networks to extract unimodal features from RGB and depth images, respectively, and then fuses them for SOD.
Exploring Modality-shared Appearance Features and Modality-invariant Relation Features for Cross-modality Person Re-Identification
Most existing cross-modality person re-identification works rely on discriminative modality-shared features for reducing cross-modality variations and intra-modality variations.
Cross-Modality Person Re-identification
Person Re-Identification
