Browse > Computer Vision > Scene Flow Estimation

Scene Flow Estimation

8 papers with code · Computer Vision

Leaderboards

No evaluation results yet. Help compare methods by submit evaluation metrics.

Greatest papers with code

Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field Estimation

ECCV 2018 NVlabs/learningrigidity

Estimation of 3D motion in a dynamic scene from a temporal pair of images is a core task in many scene understanding problems.

OPTICAL FLOW ESTIMATION SCENE FLOW ESTIMATION SCENE UNDERSTANDING

HPLFlowNet: Hierarchical Permutohedral Lattice FlowNet for Scene Flow Estimation on Large-scale Point Clouds

CVPR 2019 laoreja/HPLFlowNet

We present a novel deep neural network architecture for end-to-end scene flow estimation that directly operates on large-scale 3D point clouds.

SCENE FLOW ESTIMATION

MeteorNet: Deep Learning on Dynamic 3D Point Cloud Sequences

ICCV 2019 xingyul/meteornet

Understanding dynamic 3D environment is crucial for robotic agents and many other applications.

SCENE FLOW ESTIMATION SEMANTIC SEGMENTATION

SENSE: a Shared Encoder Network for Scene-flow Estimation

ICCV 2019 NVlabs/SENSE

We introduce a compact network for holistic scene flow estimation, called SENSE, which shares common encoder features among four closely-related tasks: optical flow estimation, disparity estimation from stereo, occlusion estimation, and semantic segmentation.

DISPARITY ESTIMATION OPTICAL FLOW ESTIMATION SCENE FLOW ESTIMATION SEMANTIC SEGMENTATION

A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation

CVPR 2016 HKBU-HPML/IRS

By combining a flow and disparity estimation network and training it jointly, we demonstrate the first scene flow estimation with a convolutional network.

DISPARITY ESTIMATION OPTICAL FLOW ESTIMATION SCENE FLOW ESTIMATION

Every Pixel Counts ++: Joint Learning of Geometry and Motion with 3D Holistic Understanding

14 Oct 2018chenxuluo/EPC

Performance on the five tasks of depth estimation, optical flow estimation, odometry, moving object segmentation and scene flow estimation shows that our approach outperforms other SoTA methods.

DEPTH ESTIMATION OPTICAL FLOW ESTIMATION SCENE FLOW ESTIMATION SEMANTIC SEGMENTATION

SceneEDNet: A Deep Learning Approach for Scene Flow Estimation

10 Jul 2018ravikt/sceneednet

This paper introduces a first effort to apply a deep learning method for direct estimation of scene flow by presenting a fully convolutional neural network with an encoder-decoder (ED) architecture.

SCENE FLOW ESTIMATION