PeterJaq
PhD, Osamu Yoshie Lab, Waseda University. Senior Perception Engineer in Bosch XC-CN.
Bosch XCShanghai,China
Pinned Repositories
adas-arxiv-daily
Awesome-Autonomous-Driving
awesome-autonomous-vehicles
Curated List of Self-Driving Cars and Autonomous Vehicles Resources
Clocs_spconv2
lidar_perception
lidar_perception_msgs
optical-film-maker
# An optical thin film design tool box
optical_film_toolbox
# Optical thin film design tools
peterjaq.github.io
yolo_parkingslot_detection
PeterJaq's Repositories
PeterJaq/Awesome-Autonomous-Driving
PeterJaq/adas-arxiv-daily
PeterJaq/lidar_perception
PeterJaq/optical_film_toolbox
# Optical thin film design tools
PeterJaq/Clocs_spconv2
PeterJaq/lidar_perception_msgs
PeterJaq/awesome-autonomous-vehicles
Curated List of Self-Driving Cars and Autonomous Vehicles Resources
PeterJaq/optical-film-maker
# An optical thin film design tool box
PeterJaq/peterjaq.github.io
PeterJaq/yolo_parkingslot_detection
PeterJaq/A-loam
PeterJaq/Awesome-BEV-Perception-Multi-Cameras
Awesome papers about Multi-Camera 3D Object Detection and Segmentation in Bird-Eye-View, such as DETR3D, BEVDet, BEVFormer
PeterJaq/awesome-lane-detection
A paper list of lane detection.
PeterJaq/CUDA-PointPillars
A project demonstrating how to use CUDA-PointPillars to deal with cloud points data from lidar.
PeterJaq/dash_clip
PeterJaq/deep_features_of_optical_constant
PeterJaq/docs-l10n
Community translations of TensorFlow documentation
PeterJaq/FAST_LIO
A computationally efficient and robust LiDAR-inertial odometry (LIO) package
PeterJaq/happy-dev-env
happy dev environment
PeterJaq/hubmap_mmsegmentation
PeterJaq/LearnTRT
PeterJaq/leetcoode_daily
personal training for code skiils in leetcode.
PeterJaq/mmdetection3d
OpenMMLab's next-generation platform for general 3D object detection.
PeterJaq/PersFormer_3DLane
[ECCV2022 Oral] Perspective Transformer on 3D Lane Detection
PeterJaq/PeterJaq
PeterJaq/tensorRT_Pro_3D
C++ library based on tensorrt integration
PeterJaq/Awesome-4D-Label-in-Autonomous-Driving
PeterJaq/BEVFormer
[ECCV 2022] This is the official implementation of BEVFormer, a camera-only framework for autonomous driving perception, e.g., 3D object detection and semantic map segmentation.
PeterJaq/DailySync
同步佳明数据至国际区和Strava。感谢 @gooin
PeterJaq/OccNet-Course
国内首个占据栅格网络全栈课程《从BEV到Occupancy Network,算法原理与工程实践》,包含端侧部署。Surrounding Semantic Occupancy Perception Course for Autonomous Driving (docs, ppt and source code) 课程主页:http://111.229.117.200:7001/