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Query Refinement Transformer for 3D Instance Segmentation
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Paper
Paper
3D Bounding Box Estimation Using Deep Learning and Geometry
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
3D \(U2\)-Net：A 3D Universal U-Net for Multi-Domain Medical Image Segmentation.md
A Combined Approach for Accurate and Accelerated Teeth Detection on Cone Beam CT Images
A Lip Sync Expert Is All You Need for Speech to Lip Generation In The Wild
A fully automatic AI system for tooth and alveolar bone segmentation from cone beam CT images
ACPL：Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image Classification
AI enabled Automatic Multimodal Fusion of Cone Beam CT and Intraoral Scans for Intelligent 3D Tooth Bone Reconstruction and Clinical Applications
Align Deep Features for Oriented Object Detection
Aligning Point Cloud Views using Persistent Feature Histograms
An End-to-End Transformer Model for 3D Object Detection
An Image is Worth 16x16 Words：Transformers for Image Recognition at Scale.md
ArcFace：Additive Angular Margin Loss for Deep Face Recognition
Attention Is All You Need
Automated Design of Deep Learning Methods for Biomedical Image Segmentation
Automated head and neck tumor segmentation from 3D PET/CT
Automatic Segmentation of Mandible from Conventional Methods to Deep Learning—A Review
BoostMIS：Boosting Medical Image Semi-supervised Learning with Adaptive Pseudo Labeling and Informative Active Annotation
Boundary loss for highly unbalanced segmentation
Center Sensitive and Boundary Aware Tooth Instance Segmentation and Classification from Cone Beam CT
Deep High-Resolution Representation Learning for Visual Recognition
Deep Hough Voting for 3D Object Detection in Point Clouds
Deep Learning for Medical Image Segmentation：Tricks, Challenges and Future Directions
Deep Learning-Based Automatic Segmentation of Mandible and Maxilla in Multi-Center CT Images
Deep Residual Learning for Image Recognition
Deep learning method for reducing metal artifacts in dental cone-beam CT using supplementary information from intra-oral scan
Densely Connected Convolutional Networks
DiRA：Discriminative, Restorative, and Adversarial Learning for Self-supervised Medical Image Analysis
DirectPose：Direct End-to-End Multi-Person Pose Estimation
End-to-End Object Detection with Transformers
Explicit Box Detection Unifies End-to-End Multi-Person Pose Estimation
Fast Facial Landmark Detection and Applications：A Survey
Fast Point Feature Histograms (FPFH) for 3D registration
Focused Decoding Enables 3D Anatomical Detection by Transformers
Frustum PointNets for 3D Object Detection from RGB-D Data
Fully Convolutional Networks for Semantic Segmentation
Fully automatic integration of dental CBCT images and full-arch intraoral impressions with stitching error correction via individual tooth segmentation and identification
Generalized Decoding for Pixel, Image, and Language
Hierarchical Morphology-Guided Tooth Instance Segmentation from CBCT Images
Highly Accurate Dichotomous Image Segmentation
Image-to-Image Translation with Conditional Adversarial Networks
Integrating Spatial Configuration into Heatmap Regression Based CNNs for Landmark Localization
Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation
Learning 3D Representations from 2D Pre-trained Models via Image-to-Point Masked Autoencoders
Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation
Mask-Attention-Free Transformer for 3D Instance Segmentation
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders As Spatiotemporal Learners
Masked attention Mask Transformer for Universal Image Segmentation
MedSegDiff：Medical Image Segmentation with Diffusion Probabilistic Model
Medical Image Segmentation Using Deep Learning：A Survey
OneFormer3D: One Transformer for Unified Point Cloud Segmentation
OneFormer: One Transformer to Rule Universal Image Segmentation
Optimized U-Net for Brain Tumor Segmentation
Per-Pixel Classification is Not All You Need for Semantic Segmentation
Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point Modeling
Polarized Self Attention：Towards High quality Pixel wise Regression
Query Refinement Transformer for 3D Instance Segmentation
Query Refinement Transformer for 3D Instance Segmentation
目录
论文
Real-Time High-Resolution Background Matting
Revisiting nnU-Net for Iterative Pseudo Labeling and Efficient Sliding Window Inference
Rich feature hierarchies for accurate object detection and semantic segmentation
Robust Reconstruction of Indoor Scenes
SUN RGB-D：A RGB-D Scene Understanding Benchmark Suite
Segment Anything
Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis
Self-Supervised Pretraining of 3D Features on any Point-Cloud
Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey
Superpoint Transformer for 3D Scene Instance Segmentation
Swin Transformer：Hierarchical Vision Transformer using Shifted Windows
Swin-Unet：Unet-like Pure Transformer for Medical Image Segmentation.md
Tooth Instance Segmentation from Cone Beam CT Images through Point based Detection and Gaussian Disentanglement
ToothNet：Automatic Tooth Instance Segmentation and Identification from Cone Beam CT Images
TotalSegmentator：robust segmentation of 104 anatomical structures in CT images.md
TransUNet：Transformers Make Strong Encoders for Medical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
\(U^2\)-Net: Going Deeper with Nested U-Structure for Salient Object Detection
UNETR：Transformers for 3D Medical Image Segmentation.md
UNeXt: MLP-based Rapid Medical Image Segmentation Network
UNet++： A Nested U Net Architecture for Medical Image Segmentation
Very Deep Convolutional Networks for Large-Scale Image Recognition
YOLO9000：Better, Faster, Stronger
YOLOv3：An Incremental Improvement
YOLOv4：Optimal Speed and Accuracy of Object Detection
YOLOv6：A Single-Stage Object Detection Framework for Industrial Applications
You Only Look Once：Unified, Real-Time Object Detection
clDice：A Novel Topology Preserving Loss Function for Tubular Structure Segmentation
nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation
Linux
Linux
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ATP简介
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Docker
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ssh连接到docker
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Deep Learning
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使用labelme标注人体关键点
损失函数
mlflow
训练MobileNetV2(mmclassification)
英伟达驱动
PyTorch学习笔记
训练SlowFast
Pytorch和MONAI中的transforms
训练YoloV5
训练YoloX
Pycoder's Weekly
Pycoder's Weekly
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641-650
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661-670
LeetCode
LeetCode
1.两数之和
11.盛最多水的容器
15.三数之和
16.最接近的三数之和
18.四数之和
26.删除有序数组中的重复项
27.移除元素
31.下一个排列
33.搜索旋转排序数组
34.在排序数组中查找元素的第一个和最后一个位置
35.搜索插入位置
36.有效的数独
37.解数独
39.组合总和
4.寻找两个正序数组的中位数
Ningx
Ningx
配置
常见问题及命令
Git
Git
Submodule
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Medical
Medical
CT图像简介
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医学影像中的重采样
医学影像文件常见格式
医学影像领域常见名词
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Other
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机器人路径规划
点云降采样
自适应蒙特卡洛定位
视频中的基础概念
目录
论文
Query Refinement Transformer for 3D Instance Segmentation
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论文
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