arXiv Computer Vision
4d ago

Deep Multimodal Fusion Detection through Spatial Mask and Channel Competition

The paper introduces an Attention-Driven Complementarity Resampling framework to enhance cross-modality object detection. It employs a shared channel spatial attention mechanism that exchanges semantic masks between modalities, encouraging the backbone to learn generalized features. Additionally, a learnable channel competition module samples and aggregates features channel‑wise, improving robustness and achieving competitive results on multiple datasets.

By Guandi Wang, Ming Li, Yunsen Xing, Junle Liu