AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
An interactive multimodal scene understanding framework based on frequency-domain dynamic routing and activation-region guidance, aiming to enhance multimodal feature representation for semantic segmentation and object detection, consistently outperforms existing approaches in image fusion, semantic segmentation, and object detection.
Infrared and visible image fusion aims to simultaneously preserve the saliency of thermal targets and rich texture details. Most existing methods primarily rely on spatial-domain representations, while the frequency-domain information is not sufficiently explored. Moreover, it remains challenging to simultaneously main...
A complementary prototype representation framework is proposed, employing three modules to collaboratively improve pseudo-label quality and improves the discriminative ability of confused categories by generating semantically similar sub-category negative samples.
Abstract. Occlusions and far distance pedestrians pose significant challenges for pedestrian detection, often leading to insufficient feature representation learned by models, which in turn results in degraded detection accuracy and a high miss rate. To address this issue, we propose a three-stage fusion multispectral...
(1) Objective: Remote sensing object detection faces significant challenges, including complex background interference, large variations in target scales, and insufficient multi-scale feature representation, which often result in missed detections of small objects, inaccurate localization, and inadequate feature fusion...
Small and dense object detection remains challenging in complex visual scenes. Repeated downsampling weakens discriminative features of tiny objects, while dense object distributions cause severe feature overlap and semantic ambiguity. To address these challenges, this paper proposes Enhanced Feature-Aware YOLO (EFA-YO...
Object detection using visible–infrared images has become increasingly important for all-day detection scenarios. However, due to significant imaging discrepancies between the visible and infrared modalities, achieving accurate modal alignment and effective feature fusion remains a major challenge. Existing methods oft...
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