
The paper introduces Deep Extrinsic Manifold Representation (DEMR), a technique that incorporates extrinsic manifold embedding into deep neural networks to generate manifold-valued outputs for various computer vision tasks. DEMR optimizes the computation graph within the embedded Euclidean space, allowing for adaptability to different architectural requirements, and avoids the direct optimization of complex geodesic losses.


coremsg

deep-learning-with-manifold-outputs-for-computer-vision-tasks


Deep Learning with Manifold Outputs for Computer Vision Tasks
