Adaptive Perception

Adaptive perception research focuses on developing systems that can robustly perceive and react to dynamic and complex environments, mirroring the adaptability of biological vision. Current efforts concentrate on improving perception models' generalization capabilities across diverse contexts and object ambiguities, often employing transformer-based architectures and adaptive algorithms for efficient processing of high-dimensional data like point clouds and 3D voxel representations. This work is crucial for advancing robotics, autonomous navigation, and computer vision applications requiring real-time responses to unpredictable situations, ultimately leading to more robust and reliable AI systems.