Ruichao Hou
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View article: Learning Frequency and Memory-Aware Prompts for Multi-Modal Object Tracking
Learning Frequency and Memory-Aware Prompts for Multi-Modal Object Tracking Open
Prompt-learning-based multi-modal trackers have made strong progress by using lightweight visual adapters to inject auxiliary-modality cues into frozen foundation models. However, they still underutilize two essentials: modality-specific f…
View article: Mamba4SOD: RGB‐T Salient Object Detection Using Mamba‐Based Fusion Module
Mamba4SOD: RGB‐T Salient Object Detection Using Mamba‐Based Fusion Module Open
RGB and thermal salient object detection (RGB‐T SOD) aims to accurately locate and segment salient objects in aligned visible and thermal image pairs. However, existing methods often struggle to produce complete masks and sharp boundaries …
View article: RGB-D Video Object Segmentation via Enhanced Multi-store Feature Memory
RGB-D Video Object Segmentation via Enhanced Multi-store Feature Memory Open
The RGB-Depth (RGB-D) Video Object Segmentation (VOS) aims to integrate the fine-grained texture information of RGB with the spatial geometric clues of depth modality, boosting the performance of segmentation. However, off-the-shelf RGB-D …
View article: X Modality Assisting RGBT Object Tracking
X Modality Assisting RGBT Object Tracking Open
Developing robust multi-modal feature representations is crucial for enhancing object tracking performance. In pursuit of this objective, a novel X Modality Assisting Network (X-Net) is introduced, which explores the impact of the fusion p…
View article: ADNet: An Asymmetric Dual-Stream Network for RGB-T Salient Object Detection
ADNet: An Asymmetric Dual-Stream Network for RGB-T Salient Object Detection Open
RGB-Thermal salient object detection (RGB-T SOD) aims to locate salient objects in images that include both RGB and thermal information. Previous approaches often suggest designing a symmetric network structure to tackle the challenge of d…
View article: RGB-D Tracking via Hierarchical Modality Aggregation and Distribution Network
RGB-D Tracking via Hierarchical Modality Aggregation and Distribution Network Open
The integration of dual-modal features has been pivotal in advancing RGB-Depth (RGB-D) tracking. However, current trackers are less efficient and focus solely on single-level features, resulting in weaker robustness in fusion and slower sp…
View article: Construction of high dynamic range image based on gradient information transformation
Construction of high dynamic range image based on gradient information transformation Open
This study proposes a fusion method for high dynamic range images based on gradient information transformation. In the proposed work, the authors first measure the three exposure weights of the source images, namely, local contrast, lumina…
View article: Brain Medical Image Fusion Based on Dual‐Branch CNNs in NSST Domain
Brain Medical Image Fusion Based on Dual‐Branch CNNs in NSST Domain Open
Computed tomography (CT) images show structural features, while magnetic resonance imaging (MRI) images represent brain tissue anatomy but do not contain any functional information. How to effectively combine the images of the two modes ha…