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Found 5 papers, 2 papers with code
ZeroFlow: Scalable Scene Flow via Distillation
Scene flow estimation is the task of describing the 3D motion field between temporally successive point clouds.
Ranked #3 on
Self-supervised Scene Flow Estimation
on Argoverse 2
Re-Evaluating LiDAR Scene Flow for Autonomous Driving
Popular benchmarks for self-supervised LiDAR scene flow (stereoKITTI, and FlyingThings3D) have unrealistic rates of dynamic motion, unrealistic correspondences, and unrealistic sampling patterns.
When to Use Convolutional Neural Networks for Inverse Problems
In this work we argue that for some types of inverse problems the CNN approximation breaks down leading to poor performance.
DeepGeo: Photo Localization with Deep Neural Network
In this paper we address the task of determining the geographical location of an image, a pertinent problem in learning and computer vision.
Deep Convolutional Compressed Sensing for LiDAR Depth Completion
In this paper we consider the problem of estimating a dense depth map from a set of sparse LiDAR points.
