9 citations · 9 across the 5 of their papers we have counts for
7 papers
SFFR: Spatial-Frequency Feature Reconstruction for Multispectral Aerial Object Detection
Xin Zuo, Chenyu Qu, Haibo Zhan +2
Recent multispectral object detection methods have primarily focused on spatial-domain feature fusion based on CNNs or Transformers, while the potential of frequency-domain feature…
JEPA-T: Joint-Embedding Predictive Architecture with Text Fusion for Image Generation
Siheng Wan, Zhengtao Yao, Zhengdao Li +9
Modern Text-to-Image (T2I) generation increasingly relies on token-centric architectures that are trained with self-supervision, yet effectively fusing text with visual tokens rema…
IRDFusion: Iterative Relation-Map Difference guided Feature Fusion for Multispectral Object Detection
Jifeng Shen, Haibo Zhan, Xin Zuo +4
Current multispectral object detection methods often retain extraneous background or noise during feature fusion, limiting perceptual performance. To address this, we propose an in…
C3-OWD: A Curriculum Cross-modal Contrastive Learning Framework for Open-World Detection
Siheng Wang, Zhengdao Li, Yanshu Li +12
Object detection has advanced significantly in the closed-set setting, but real-world deployment remains limited by two challenges: poor generalization to unseen categories and ins…
InceptionMamba: An Efficient Hybrid Network with Large Band Convolution and Bottleneck Mamba
Yuhang Wang, Jun Li, Zhijian Wu +3
Within the family of convolutional neural networks, InceptionNeXt has shown excellent competitiveness in image classification and a number of downstream tasks. Built on parallel on…
Multispectral State-Space Feature Fusion: Bridging Shared and Cross-Parametric Interactions for Object Detection
Jifeng Shen, Haibo Zhan, Shaohua Dong +3
Modern multispectral feature fusion for object detection faces two critical limitations: (1) Excessive preference for local complementary features over cross-modal shared semantics…