| yzcjtr/GeoNet |
579 |
|
0 |
0 |
about 7 years ago |
0 |
|
3 |
mit |
Python |
| Code for GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose (CVPR 2018) |
| daniilidis-group/EV-FlowNet |
69 |
|
0 |
0 |
over 6 years ago |
0 |
|
4 |
other |
Python |
| Code for the paper "EV-FlowNet: Self-Supervised Optical Flow for Event-based Cameras" |
| MungoMeng/Panorama-OpticalFlow |
48 |
|
0 |
0 |
almost 4 years ago |
0 |
|
3 |
mit |
C++ |
| A panorama stitching algorithm based on asymmetric bidirectional optical flow. |
| better-flow/evimo |
39 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
gpl-3.0 |
C++ |
| A toolkit for dataset generation with event-based cameras |
| aoso3/Real-Time-Abnormal-Events-Detection-and-Tracking-in-Surveillance-System |
30 |
|
0 |
0 |
over 4 years ago |
0 |
|
1 |
mit |
C# |
| The main abnormal behaviors that this project can detect are: Violence, covering camera, Choking, lying down, Running, Motion in restricted areas. It provides much flexibility by allowing users to choose the abnormal behaviors they want to be detected and keeps track of every abnormal event to be reviewed. We used three methods to detect abnormal behaviors: Motion influence map, Pattern recognition models, State event model. For multi-camera tracking, we combined a single camera tracking algorithm with a spatial based algorithm. |
| PX4/snap_cam |
20 |
|
0 |
0 |
over 7 years ago |
0 |
|
4 |
|
C++ |
| This package provides tools to work with the Snapdragon Flight cameras as well as perform optical flow for use with the PX4 flight stack. |
| EthanZhu90/MultilayerBSMC_ICCV17 |
16 |
|
0 |
0 |
almost 8 years ago |
0 |
|
2 |
mit |
C++ |
| Code for ICCV'17 "A Multilayer-Based Framework for Online Background Subtraction with Freely Moving Cameras" |
| intel-aero/aero-optical-flow |
8 |
|
0 |
0 |
over 3 years ago |
0 |
|
3 |
bsd-3-clause |
C++ |
| nagrjungururaj/Semantic-Motion-Segmentation-using-Optical-flow-and-Convolutional-Neural-Networks |
6 |
|
0 |
0 |
about 7 years ago |
0 |
|
0 |
|
MATLAB |
| Semantic Motion Segmentation using Optical flow and Convolutional Neural Networks |
| RCmags/ADNS3080 |
6 |
|
0 |
0 |
about 3 years ago |
0 |
|
1 |
mit |
C++ |
| Arduino library for the ADNS3080 mouse sensor |
