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3d-bat

3D Bounding Box Annotation Tool (3D-BAT) Point cloud and Image Labeling

3dvision

bbavectors-oriented-object-detection

[WACV2021] Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors

birds-eye-view

Obtain bird's eye view of a scene from a single input image

build-locally

gndnet

GndNet: Fast ground plane estimation and point cloud segmentation for autonomous vehicles using deep neural networks.

homepage

Yunhe Wang's HomePage

losses-for-object-detection

A comprehensive review of losses functions used for object detection task.

markdown_readme

Markdown - you can mark up titles, lists, tables, etc., in a much cleaner, readable and accurate way if you do it with HTML.

models

Pre-trained and Reproduced Deep Learning Models （『飞桨』官方模型库，包含多种学术前沿和工业场景验证的深度学习模型）

object3d

Code for "6-DoF Object Pose from Semantic Keypoints", ICRA 2017

objectdetectionimbalance

Lists the papers related to imbalance problems in object detection [TPAMI]

phd_thesis

pv-ssd

The proposed approach enhances the CenterPoint baseline with a multimodal fusion mechanism. First, inspired by PointPainting, an off-the-shelf Mask-RCNN model trained from nuImages is employed to generate 2D object mask information based on the camera images. Furthermore, the Cylinder3D is also adopted to produce the 3D semantic information of the input LiDAR point cloud. Then, an improved version of CenterPoint takes the painted points(with 2D instance segmentation and 3D semantic segmentation) as inputs for accurate object detection. Specifically, we replace the RPN module in CenterPoint with modified Spatial-Semantic Feature Aggregation(SSFA) to well address multi-class detection. A simple pseudo labeling technique is also integrated in a semi-supervised learning manner. In addition, the Test Time Augmentation(TTA) strategy including multiple flip and rotation operations is applied during the inference time. Finally, the detections generated from multiple voxel resolutions (0.05m to 0.125m) are assembled with 3D Weighted Bounding Box Fusion(WBF) technique to produce the final results.

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

random-forest-matlab

A Random Forest implementation for MATLAB. Supports arbitrary weak learners that you can define.

redner

Differentiable rendering without approximation.

rotated_iou

Differentiable IoU of rotated bounding boxes using Pytorch

s2anet

Official code of the paper "Align Deep Features for Oriented Object Detection"

semantic-segmentation-editor

Web labeling tool for bitmap images and point clouds

sfa3d

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