Advances in Feed-Forward 3D Reconstruction and View Synthesis: A Survey

Recent advancements in feed-forward 3D reconstruction and view synthesis are significantly impacting the fields of computer vision and immersive technologies such as augmented reality (AR) and virtual reality (VR) (F1, F2). Traditional methods for these processes were often slow and complex, limiting their practical applications (F3). However, new deep learning techniques have been developed that improve the speed and efficiency of 3D reconstruction and view synthesis (A1, F4). These improvements are opening up exciting possibilities for real-world applications, enhancing the usability and accessibility of AR and VR technologies (F5). The integration of these advanced methods marks a transformative shift from earlier approaches, enabling faster and more efficient workflows. This progress aligns with ongoing research trends emphasizing the role of deep learning in advancing computer vision capabilities. Overall, these developments suggest a promising future for immersive technologies driven by improved 3D reconstruction and view synthesis techniques.