3 accepted papers
Fine-grained anomaly detection is crucial in industrial and medical applications, but labeled anomalies are often scarce, making zero-shot detection challenging. While vision-language models like CLIP offer promising solutions, they struggle with foreground-background feature entanglement and coarse
Co-training has achieved significant success in the field of semi-supervised learning; however, the *homogenization phenomenon*, which arises from multiple models tending towards similar decision boundaries, remains inadequately addressed. To tackle this issue, we propose a novel algorithm called **…
We present VG-Swarm, a practical and effective method for aerial robots dynamic encirclement, which consists of a vision-based gene regulatory network (V-GRN) and a visual perception module. For each flying robot deployed with the proposed method, the relative spatial positions of the surrounding ro