Multi Camera
Multi-camera systems aim to leverage information from multiple viewpoints to improve computer vision tasks beyond the capabilities of single-camera systems. Current research focuses on robust data association across cameras, often employing graph neural networks or transformer-based architectures to handle challenges like occlusion and varying viewpoints, and developing efficient 3D multi-object tracking and scene reconstruction methods. These advancements have significant implications for applications such as autonomous driving, robotics, surveillance, and 3D modeling, enabling more accurate and reliable perception and understanding of complex scenes.
Papers
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