三維目標檢測入門
- 1 文檔需知
- 2 基礎知識
- 深度學習基礎必上手項目
- 科研研究必知道的論文門戶
- 深度學習必看論文
- 3 目標檢測入門知識
- 二維目標檢測必看論文
- 4 三維目標檢測入門知識
- 三維目標檢測必熟悉數據集
- 三維目標檢測點云分類分割預備知識
- 三維目標檢測必熟悉,必跑通,必理解細節實現的框架
- 三維目標檢測必看(有時間必復現)論文(都有開源代碼)
1 文檔需知
本文檔為實驗室整理,僅供學習使用。未經允許嚴禁私自轉載。
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三維目標檢測入門
2 基礎知識
- 機器學習(機器學習(西瓜書)周志華, 吳恩達系列視頻)
- 深度學習 (李飛飛系列視頻,各種深度學習實戰書籍)
- Python 編程基礎 (網易云課堂搜索 python 基礎)
- Pytorch 深度學習框架 (pytorch 實戰書籍)
深度學習基礎必上手項目
- MNIST 手寫數字識別
- Cifar10 圖像分類項目
科研研究必知道的論文門戶
- 谷歌學術:https://scholar.google.com
- Arxiv:https://arxiv.org/
- 語義學術:https://www.semanticscholar.org/
- 微軟學術:https://academic.research.microsoft.com/
深度學習必看論文
- VGG:Very Deep Convolutional Networks for Large-Scale Image Recognition
- ResNet: Deep Residual Learning for Image Recognition
- BatchNorm:Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- Adam:Adam: A Method for Stochastic Optimization
- LSTM:Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
- Transformer:Attention Is All You Need
3 目標檢測入門知識
二維目標檢測必看論文
- R-CNN
- Fast R-CNN
- Faster R-CNN
- YOLO 系列
- SSD 系列
4 三維目標檢測入門知識
三維目標檢測必熟悉數據集
- KITTI
- Nuscence
- Waymo
三維目標檢測點云分類分割預備知識
- PointNet (必手撕代碼)
- PointNet++
三維目標檢測必熟悉,必跑通,必理解細節實現的框架
- OpenPCDet
- Det3D
三維目標檢測必看(有時間必復現)論文(都有開源代碼)
- SECOND:Sparsely Embedded Convolutional Detection
- VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
- PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud
- PointPillars: Fast Encoders for Object Detection from Point Clouds
- 3DSSD: Point-based 3D Single Stage Object Detector
- SA-SSD:Structure Aware Single-stage 3D Object Detection from Point Cloud
- PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
- Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection
- Center-based 3D Object Detection and Tracking
- SE-SSD: Self-Ensembling Single-Stage Object Detector From Point Cloud
- Voxel Transformer for 3D Object Detection
- Improving 3D Object Detection with Channel-wise Transformer
- Behind the Curtain: Learning Occluded Shapes for 3D Object Detection
- Sparse Fuse Dense: Towards High Quality 3D Detection with Depth
Completion - DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets
- SAFDNet: A Simple and Effective Network for Fully Sparse 3D Object Detection