Enhancing Camouflaged Object Detectors with Camouflageator and ICEG
The author proposes the use of Camouflageator and ICEG to improve camouflaged object detection by generating more deceptive objects and addressing segmentation issues.
Preys and Predators in Camouflaged Object Detection: A Novel Approach
Enhancing camouflaged object detectors through adversarial training and feature coherence.
Preys and Predators in Camouflaged Object Detection
Preys develop better camouflage, predators acquire acute vision.
Strategische Beute machen scharfe Raubtiere: Verbesserung von getarnten Objektdetektoren durch die Erzeugung getarnter Objekte
Algorithmen zur Verbesserung von getarnten Objektdetektoren durch die Erzeugung getarnter Objekte.
Efficient Single-branch Network for Camouflaged Object Detection via Spotlight Shifting Co-supervision
A novel single-branch network, Co-Supervised Spotlight Shifting Network (CS3Net), efficiently leverages a spotlight shifting strategy for co-supervision to enhance the detection of camouflaged objects.
Adaptive Guidance Learning Network for Accurate Camouflaged Object Detection
The proposed adaptive guidance learning network (AGLNet) can effectively explore and integrate various additional cues, such as boundary, texture, edge, and frequency information, to guide the learning of camouflaged features for accurate object detection.
Collaborative Optimization Strategy for Effective Camouflaged Object Detection
A novel collaborative optimization strategy that simultaneously models long-range dependencies and local details to generate high-quality features for accurate detection of camouflaged objects.
Frequency-Guided Spatial Adaptation for Enhancing Camouflaged Object Detection
A novel frequency-guided spatial adaptation method is proposed to enhance the feature representation for accurately detecting camouflaged objects by dynamically adjusting the frequency components to focus more on the concealed regions.
Hierarchical Graph Interaction Transformer with Dynamic Token Clustering for Effective Camouflaged Object Detection
The proposed HGINet model can effectively discover imperceptible camouflaged objects by employing a hierarchical graph interaction mechanism and dynamic token clustering strategy.
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