Paper interpretation | Original PV-RCNN network for 3D object detection - Code World

Paper interpretation | Original PV-RCNN network for 3D object detection

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Origin blog.csdn.net/Hinyeung2021/article/details/132814780

Paper interpretation | Original PV-RCNN network for 3D object detection

[3D Detection Series-PV-RCNN] Detailed explanation of PV-RCNN paper, PV-RCNN code reproduction, including official website PV-RCNN pre-training weights and error reporting issues

Interpretation of the paper｜VoxelNet: End-to-end learning for point cloud-based 3D object detection

Paper Interpretation | Center-based 3D Object Detection and Tracking

MonoDETR: Depth-guided Transformer for Monocular 3D Object Detection Paper Interpretation

[Interpretation of the paper] Camouflaged Object Detection

[Paper Notes] PillarNeXt: Rethinking Network Designs for 3D Object Detection in LiDAR Point Clouds

Paper Interpretation--K-Radar: 4D Radar Object Detection for Autonomous Driving in Various Weather Conditions

VoxelNext, a fully sparse 3D object detection network

Interpretation of the paper: End-to-End Object Detection with Transformers

Paper Interpretation--CNN based Road User Detection using the 3D Radar Cube

Paper's EfficientDet: Translation and Interpretation of "Scalable and Efficient Object Detection—Scalable and Efficient Object Detection"—Sequel

[Target detection] Target detection meets knowledge graph: Interpretation and reproduction of Object detection meets knowledge graphs paper

Target detection algorithm: Faster-RCNN paper interpretation

Paper reading-Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Image

3D box classic paper - "Multimodal 3D Object Detection from Simulated Pretraining" learning record

Paper reading: "Bridging the Gap in 3D Object Detection for Autonomous Driving"

Paper reading: EPNet: Enhancing Point Features with ImageSemantics for 3D Object Detection

Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detection - Paper Notes

[Paper Notes] MonoNeRD: NeRF-like Representations for Monocular 3D Object Detection

[Paper Notes] Cross Modal Transformer: Towards Fast and Robust 3D Object Detection

[Paper Notes] SVDM: Single-View Diffusion Model for Pseudo-Stereo 3D Object Detection

Interpretation of the paper detection target 3 - Fast R-CNN

[Paper Notes] SAM3D: Zero-Shot 3D Object Detection via Segment Anything Model

[3D Detection Series-PV-RCNN] Подробное объяснение статьи PV-RCNN, воспроизведение кода PV-RCNN, включая весовые коэффициенты предварительного обучения PV-RCNN на официальном сайте и проблемы с отчетами об ошибках.

Multi-View 3D Object Detection Network for Autonomous Driving

Interpretation of "You Only Look Once: Unified, Real-Time Object Detection" YOLOV1 paper

Paper interpretation | YOLO series pioneering work: unified real-time object detection

Interpretation of the paper--PointPillars- Fast Encoders for Object Detection from Point Clouds

VISTA Boosting 3D Object Detection via Dual Cross-VIew SpaTial Attention paper personal summary

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