RT-DETR++ for UAV Object Detection

• URL: http://arxiv.org/abs/2509.09157v1
• Date: Thu, 11 Sep 2025 05:33:52 GMT
• Title: RT-DETR++ for UAV Object Detection
• Authors: Yuan Shufang,
• Abstract summary: This paper introduces RT-DETR++, which enhances the encoder component of the RT-DETR model.<n>We introduce a channel-gated attention-based upsampling/downsampling mechanism.<n>Second, we incorporate CSP-PAC during feature fusion.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Object detection in unmanned aerial vehicle (UAV) imagery presents significant challenges. Issues such as densely packed small objects, scale variations, and occlusion are commonplace. This paper introduces RT-DETR++, which enhances the encoder component of the RT-DETR model. Our improvements focus on two key aspects. First, we introduce a channel-gated attention-based upsampling/downsampling (AU/AD) mechanism. This dual-path system minimizes errors and preserves details during feature layer propagation. Second, we incorporate CSP-PAC during feature fusion. This technique employs parallel hollow convolutions to process local and contextual information within the same layer, facilitating the integration of multi-scale features. Evaluation demonstrates that our novel neck design achieves superior performance in detecting small and densely packed objects. The model maintains sufficient speed for real-time detection without increasing computational complexity. This study provides an effective approach for feature encoding design in real-time detection systems.

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