Dense Scene

Dense scene understanding aims to comprehensively analyze and reconstruct 3D scenes from various sensor inputs, enabling applications like autonomous driving and virtual/augmented reality. Current research heavily focuses on multi-task learning using advanced architectures like transformers and novel decoder designs (e.g., Mamba-based decoders) to efficiently handle long-range dependencies and cross-task interactions within complex scenes. These advancements address challenges in accurate depth estimation, robust pose estimation, and scalable scene representation, particularly for large-scale environments and scenarios involving incomplete or noisy data, ultimately improving the accuracy and robustness of 3D scene reconstruction.