Real World Stereo Signal

Real-world stereo signal processing focuses on accurately capturing and interpreting information from two-channel audio or visual recordings to reconstruct three-dimensional scenes or enhance audio quality. Current research emphasizes developing robust algorithms, such as deep learning models employing continuous risk minimization or vision transformers with cross-attention mechanisms, to address challenges like disparity estimation in stereo vision and accurate source separation in stereo audio. These advancements improve applications ranging from 3D scene reconstruction in robotics and virtual reality to enhancing the realism of synthesized audio and improving the accuracy of audio scene analysis. The ultimate goal is to create more natural and immersive experiences across various multimedia applications.