Camera Based Perception

Camera-based perception focuses on using computer vision to enable machines to "see" and understand their environment, primarily for applications like autonomous driving and robotics. Current research emphasizes improving robustness and efficiency, addressing challenges like camera motion (through stabilization techniques) and adversarial attacks (by developing more resilient models). Key areas of focus include developing accurate 3D object detection from single or multiple cameras, often employing bird's-eye-view representations and self-supervised calibration methods to reduce reliance on manual calibration. These advancements are crucial for enhancing the safety and reliability of autonomous systems and expanding the capabilities of robots in complex environments.