PACGNet: Pyramidal Adaptive Cross-Gating Network for Multimodal Object Detection in Aerial Imagery

arXiv:2512.18291 · cs.CV · Submitted 2025-12-20 · Read on arXiv

cs.CV

Submitted: 2025-12-20

Updated: 2026-09-26

Code: https://github.com/Alianess/PACGNet

Terminology

• Benchmark — 13× in this paper · explained in 2 episodes
• Pyramidal Feature-aware Multimodal Gating — 11× in this paper
• Symmetrical Cross-Gating — 11× in this paper
• Alignment — 9× in this paper · explained in 1 episode
• Core — 9× in this paper · explained in 2 episodes
• Transformer — 8× in this paper · explained in 2 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Multimodal Fusion — 5× in this paper · explained in 3 episodes
• Ablation study — 4× in this paper · explained in 1 episode
• Aggregation — 4× in this paper · explained in 1 episode
• Attention Mechanism — 4× in this paper · explained in 2 episodes
• Loss Function — 4× in this paper · explained in 2 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Feature Extraction — 3× in this paper · explained in 2 episodes
• Interpretability — 3× in this paper · explained in 15 episodes
• Redundancy — 3× in this paper · explained in 2 episodes
• Convolutional Block Attention Module — 2× in this paper
• Path Aggregation Network — 2× in this paper
• Quantization — 2× in this paper · explained in 12 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adaptive Weighting — 1× in this paper · explained in 1 episode
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Feature Selection — 1× in this paper · explained in 4 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Instance Segmentation — 1× in this paper · explained in 3 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Stochastic Gradient Descent (SGD) — 1× in this paper · explained in 5 episodes
• Two-Stage Architecture — 1× in this paper · explained in 2 episodes

Sources

• UAV-DETR: Efficient End-to-End Object Detection for Unmanned Aerial Vehicle Imagery
• Selective Structured State Space for Multispectral-fused Small Target Detection
• Multispectral Deep Neural Networks for Pedestrian Detection
• Multispectral Pedestrian Detection via Simultaneous Detection and Segmentation
• Anchor-free Small-scale Multispectral Pedestrian Detection
• Cross-Modality Fusion Transformer for Multispectral Object Detection
• Wise-IoU: Bounding Box Regression Loss with Dynamic Focusing Mechanism

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