Mem3R: Streaming 3D Reconstruction with Hybrid Memory via Test-Time Training

ArXi:2604.07279v1 Announce Type: new Streaming 3D perception is well suited to robotics and augmented reality, where long visual streams must be processed efficiently and consistently. Recent recurrent models offer a promising solution by maintaining fixed-size states and enabling linear-time inference, but they often suffer from drift accumulation and temporal forgetting over long sequences due to the limited capacity of compressed latent memories.