# reading

**Repository Path**: feixyz/reading

## Basic Information

- **Project Name**: reading
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-04-16
- **Last Updated**: 2021-04-16

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Papers, Books, Blogs, Talks, Courses and Git-repos

## SLAM
- [__book__] 视觉Slam十四讲 [:star:]
- [On-Manifold Preintegration for Real-Time Visual-Inertial Odometry](https://arxiv.org/abs/1512.02363) 
- [LOAM: Lidar Odometry and Mapping in Real-time](https://www.ri.cmu.edu/pub_files/2014/7/Ji_LidarMapping_RSS2014_v8.pdf) 
- *[Others](lists/slam.md)*

## Visual 3D Perception
- [3D Bounding Box Estimation Using Deep Learning and Geometry](https://openaccess.thecvf.com/content_cvpr_2017/papers/Mousavian_3D_Bounding_Box_CVPR_2017_paper.pdf) [__CVPR2017__]
- [RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving](https://arxiv.org/pdf/2001.03343.pdf) 
- *[Others](lists/visual3d_perception.md)*

## Lidar Perception
- [PointPillars: Fast Encoders for Object Detection from Point Clouds](https://openaccess.thecvf.com/content_CVPR_2019/papers/Lang_PointPillars_Fast_Encoders_for_Object_Detection_From_Point_Clouds_CVPR_2019_paper.pdf) [__CVPR2019__]
- *[Others](lists/lidar_perception.md)*

## Fusion
- [Frustum PointNets for 3D Object Detection from RGB-D Data](http://openaccess.thecvf.com/content_cvpr_2018/papers/Qi_Frustum_PointNets_for_CVPR_2018_paper.pdf) [__CVPR2018__]
- *[Others](lists/fusion.md)*

## Tracking
- [Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics](https://link.springer.com/content/pdf/10.1155/2008/246309.pdf)
- *[Others](lists/tracking.md)*

## Depth and Flow
- [Unsupervised Learning of Depth, Optical Flow and Pose with Occlusion from 3D Geometry](https://arxiv.org/pdf/2003.00766.pdf) [:star:] 
- *[Others](lists/depth_flow.md)*

## Keypoint
- [SuperPoint: Self-Supervised Interest Point Detection and Description](http://openaccess.thecvf.com/content_cvpr_2018_workshops/papers/w9/DeTone_SuperPoint_Self-Supervised_Interest_CVPR_2018_paper.pdf) [__CVPR2018__]
- *[Others](lists/keypoint.md)*

## Dataset
- [Vision meets Robotics: The KITTI Dataset](http://ww.cvlibs.net/publications/Geiger2013IJRR.pdf) [__IJRR2013__]
- [Scalability in Perception for Autonomous Driving: Waymo Open Dataset](https://openaccess.thecvf.com/content_CVPR_2020/papers/Sun_Scalability_in_Perception_for_Autonomous_Driving_Waymo_Open_Dataset_CVPR_2020_paper.pdf) [__CVPR2020__]
- [nuScenes: A multimodal dataset for autonomous driving](http://openaccess.thecvf.com/content_CVPR_2020/papers/Caesar_nuScenes_A_Multimodal_Dataset_for_Autonomous_Driving_CVPR_2020_paper.pdf) [__CVPR2020__]
- *[Others](lists/dataset.md)*

## Calibration
- [Automatic Online Calibration of Cameras and Lasers](http://www.roboticsproceedings.org/rss09/p29.pdf)
- *[Others](lists/calibration.md)*

## Object Detection and Segmentation
- [Mask R-CNN](http://openaccess.thecvf.com/content_ICCV_2017/papers/He_Mask_R-CNN_ICCV_2017_paper.pdf) [__CVPR2017__]
- [Objects as Points](https://arxiv.org/pdf/1904.07850.pdf)
- *[Others](lists/object_det2d_segmentation.md)*

## General Deep Learning
- *[Others](lists/general_dl.md)*

## Lane
- *[Others](lists/lane.md)*