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Found 4 papers, 2 papers with code
Neural Trajectory Fields for Dynamic Novel View Synthesis
Recent approaches to render photorealistic views from a limited set of photographs have pushed the boundaries of our interactions with pictures of static scenes.
DeepGMR: Learning Latent Gaussian Mixture Models for Registration
Point cloud registration is a fundamental problem in 3D computer vision, graphics and robotics.
EOE: Expected Overlap Estimation over Unstructured Point Cloud Data
We present an iterative overlap estimation technique to augment existing point cloud registration algorithms that can achieve high performance in difficult real-world situations where large pose displacement and non-overlapping geometry would otherwise cause traditional methods to fail.
Fast and Accurate Point Cloud Registration using Trees of Gaussian Mixtures
Point cloud registration sits at the core of many important and challenging 3D perception problems including autonomous navigation, SLAM, object/scene recognition, and augmented reality.
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