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A collection of deep learning based localization models

OpenPCDet Toolbox for LiDAR-based 3D Object Detection.

SA-Det3D: Self-attention based Context-Aware 3D Object Detection

🔥 💪 🤘 My summary of awesome-semantic-segmentation

Super Fast and Accurate 3D Object Detection based on 3D LiDAR Point Clouds (The PyTorch implementation)

Weakly Supervised Framework for 3D Scene Understanding-European Conference on Computer Vision 22

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

Kernel Point Convolutions

Attentional-PointNet is Deep-Neural-Network architecture for 3D object detection in point clouds

DepthContrast self-supervised learning for 3D

Deep learning inference nodes for ROS with support for NVIDIA Jetson TX1/TX2/Xavier and TensorRT

🔥3D-BoNet in Tensorflow (NeurIPS 2019, Spotlight)

UAV Simulation Platform based on PX4, ROS and Gazebo

LiDAR-inertial SLAM: Scan Context + LIO-SAM

Pytorch framework for doing deep learning on point clouds.

Caffe implementation of Google MobileNet SSD detection network, with pretrained weights on VOC0712 and mAP=0.727.

Detectron2 is FAIR's next-generation research platform for object detection and segmentation.

Datasets, Transforms and Models specific to Computer Vision

A very simple framework for state-of-the-art Natural Language Processing (NLP)

Minimal PyTorch implementation of YOLOv3