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python开发界面程序，CVPR2024 论文和代码合集，作为一名程序员我不忘初心_含有python编程代码的论文

作者：IT小白 | 2024-06-22 14:40:21

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含有python编程代码的论文

视频目标检测
目标跟踪
- 多目标跟踪
语义分割
实例分割
全景分割
视频目标分割
超像素分割
交互式图像分割
NAS
GAN
Re-ID
3D点云（分类/分割/配准等）
- 3D点云卷积
3D点云分类
3D点云语义分割
3D点云实例分割
3D点云配准
3D点云补全
3D点云目标跟踪
其他
人脸
- 人脸识别
人脸检测
人脸活体检测
人脸表情识别
人脸转正
人脸3D重建
人体姿态估计(2D/3D)
- 2D人体姿态估计
3D人体姿态估计
人体解析
场景文本检测
场景文本识别
特征(点)检测和描述
超分辨率
- 图像超分辨率
视频超分辨率
模型压缩/剪枝
视频理解/行为识别
- 基于骨架的动作识别
人群计数
深度估计
- 单目深度估计
6D目标姿态估计
手势估计
显著性检测
去噪
去雨
去模糊
- 视频去模糊
去雾
特征点检测与描述
视觉问答(VQA)
视频问答(VideoQA)
视觉语言导航
视频压缩
视频插帧
风格迁移
车道线检测
"人-物"交互(HOT)检测
轨迹预测
运动预测
光流估计
图像检索
虚拟试衣
HDR
对抗样本
三维重建
深度补全
语义场景补全
图像/视频描述
线框解析
数据集
其他
不确定中没中

CNN

==============================================================

Exploring Self-attention for Image Recognition

论文：https://hszhao.github.io/papers/cvpr20_san.pdf
代码：https://github.com/hszhao/SAN

Improving Convolutional Networks with Self-Calibrated Convolutions

主页：https://mmcheng.net/scconv/
论文：http://mftp.mmcheng.net/Papers/20cvprSCNet.pdf
代码：https://github.com/backseason/SCNet

Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNets

论文：https://arxiv.org/abs/2003.13549
代码：https://github.com/zeiss-microscopy/BSConv

图像分类

===============================================================

Interpretable and Accurate Fine-grained Recognition via Region Grouping

论文：https://arxiv.org/abs/2005.10411
代码：https://github.com/zxhuang1698/interpretability-by-parts

Compositional Convolutional Neural Networks: A Deep Architecture with Innate Robustness to Partial Occlusion

论文：https://arxiv.org/abs/2003.04490
代码：https://github.com/AdamKortylewski/CompositionalNets

Spatially Attentive Output Layer for Image Classification

论文：https://arxiv.org/abs/2004.07570
代码（好像被原作者删除了）：https://github.com/ildoonet/spatially-attentive-output-layer

视频分类

===============================================================

SmallBigNet: Integrating Core and Contextual Views for Video Classification

论文：https://arxiv.org/abs/2006.14582
代码：https://github.com/xhl-video/SmallBigNet

目标检测

===============================================================

Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax

论文：http://openaccess.thecvf.com/content_CVPR_2020/papers/Li_Overcoming_Classifier_Imbalance_for_Long-Tail_Object_Detection_With_Balanced_Group_CVPR_2020_paper.pdf
代码：https://github.com/FishYuLi/BalancedGroupSoftmax

AugFPN: Improving Multi-scale Feature Learning for Object Detection

论文：http://openaccess.thecvf.com/content_CVPR_2020/papers/Guo_AugFPN_Improving_Multi-Scale_Feature_Learning_for_Object_Detection_CVPR_2020_paper.pdf
代码：https://github.com/Gus-Guo/AugFPN

Noise-Aware Fully Webly Supervised Object Detection

论文：http://openaccess.thecvf.com/content_CVPR_2020/html/Shen_Noise-Aware_Fully_Webly_Supervised_Object_Detection_CVPR_2020_paper.html
代码：https://github.com/shenyunhang/NA-fWebSOD/

Learning a Unified Sample Weighting Network for Object Detection

论文：https://arxiv.org/abs/2006.06568
代码：https://github.com/caiqi/sample-weighting-network

D2Det: Towards High Quality Object Detection and Instance Segmentation

论文：http://openaccess.thecvf.com/content_CVPR_2020/papers/Cao_D2Det_Towards_High_Quality_Object_Detection_and_Instance_Segmentation_CVPR_2020_paper.pdf
代码：https://github.com/JialeCao001/D2Det

Dynamic Refinement Network for Oriented and Densely Packed Object Detection

论文下载链接：https://arxiv.org/abs/2005.09973
代码和数据集：https://github.com/Anymake/DRN_CVPR2020

Scale-Equalizing Pyramid Convolution for Object Detection

论文：https://arxiv.org/abs/2005.03101

代码：https://github.com/jshilong/SEPC

Revisiting the Sibling Head in Object Detector

论文：https://arxiv.org/abs/2003.07540
代码：https://github.com/Sense-X/TSD

Scale-equalizing Pyramid Convolution for Object Detection

论文：暂无
代码：https://github.com/jshilong/SEPC

Detection in Crowded Scenes: One Proposal, Multiple Predictions

论文：https://arxiv.org/abs/2003.09163
代码：https://github.com/megvii-model/CrowdDetection

Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object Detection

论文：https://arxiv.org/abs/2004.04725
代码：https://github.com/NVlabs/wetectron

Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection

论文：https://arxiv.org/abs/1912.02424
代码：https://github.com/sfzhang15/ATSS

BiDet: An Efficient Binarized Object Detector

论文：https://arxiv.org/abs/2003.03961
代码：https://github.com/ZiweiWangTHU/BiDet

Harmonizing Transferability and Discriminability for Adapting Object Detectors

论文：https://arxiv.org/abs/2003.06297
代码：https://github.com/chaoqichen/HTCN

CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection

论文：https://arxiv.org/abs/2003.09119
代码：https://github.com/KiveeDong/CentripetalNet

Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection

论文：https://arxiv.org/abs/2003.11818
代码：https://github.com/ggjy/HitDet.pytorch

EfficientDet: Scalable and Efficient Object Detection

论文：https://arxiv.org/abs/1911.09070
代码：https://github.com/google/automl/tree/master/efficientdet

3D目标检测

=================================================================

SESS: Self-Ensembling Semi-Supervised 3D Object Detection

论文： https://arxiv.org/abs/1912.11803
代码：https://github.com/Na-Z/sess

Associate-3Ddet: Perceptual-to-Conceptual Association for 3D Point Cloud Object Detection

论文： https://arxiv.org/abs/2006.04356
代码：https://github.com/dleam/Associate-3Ddet

What You See is What You Get: Exploiting Visibility for 3D Object Detection

主页：https://www.cs.cmu.edu/~peiyunh/wysiwyg/
论文：https://arxiv.org/abs/1912.04986
代码：https://github.com/peiyunh/wysiwyg

Learning Depth-Guided Convolutions for Monocular 3D Object Detection

论文：https://arxiv.org/abs/1912.04799
代码：https://github.com/dingmyu/D4LCN

Structure Aware Single-stage 3D Object Detection from Point Cloud

论文：http://openaccess.thecvf.com/content_CVPR_2020/html/He_Structure_Aware_Single-Stage_3D_Object_Detection_From_Point_Cloud_CVPR_2020_paper.html
代码：https://github.com/skyhehe123/SA-SSD

IDA-3D: Instance-Depth-Aware 3D Object Detection from Stereo Vision for Autonomous Driving

论文：http://openaccess.thecvf.com/content_CVPR_2020/papers/Peng_IDA-3D_Instance-Depth-Aware_3D_Object_Detection_From_Stereo_Vision_for_Autonomous_CVPR_2020_paper.pdf
代码：https://github.com/swords123/IDA-3D

Train in Germany, Test in The USA: Making 3D Object Detectors Generalize

论文：https://arxiv.org/abs/2005.08139
代码：https://github.com/cxy1997/3D_adapt_auto_driving

MLCVNet: Multi-Level Context VoteNet for 3D Object Detection

论文：https://arxiv.org/abs/2004.05679
代码：https://github.com/NUAAXQ/MLCVNet

3DSSD: Point-based 3D Single Stage Object Detector

CVPR 2020 Oral
论文：https://arxiv.org/abs/2002.10187
代码：https://github.com/tomztyang/3DSSD

Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation

论文：https://arxiv.org/abs/2004.03572
代码：https://github.com/zju3dv/disprcn

End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection

论文：https://arxiv.org/abs/2004.03080
代码：https://github.com/mileyan/pseudo-LiDAR_e2e

DSGN: Deep Stereo Geometry Network for 3D Object Detection

论文：https://arxiv.org/abs/2001.03398
代码：https://github.com/chenyilun95/DSGN

LiDAR-based Online 3D Video Object Detection with Graph-based Message Passing and Spatiotemporal Transformer Attention

论文：https://arxiv.org/abs/2004.01389
代码：https://github.com/yinjunbo/3DVID

PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection

论文：https://arxiv.org/abs/1912.13192
代码：https://github.com/sshaoshuai/PV-RCNN

Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud

论文：https://arxiv.org/abs/2003.01251
代码：https://github.com/WeijingShi/Point-GNN

视频目标检测

=================================================================

Memory Enhanced Global-Local Aggregation for Video Object Detection

论文：https://arxiv.org/abs/2003.12063

代码：https://github.com/Scalsol/mega.pytorch

目标跟踪

===============================================================

SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking

论文：https://arxiv.org/abs/1911.07241
代码：https://github.com/ohhhyeahhh/SiamCAR

D3S – A Discriminative Single Shot Segmentation Tracker

论文：https://arxiv.org/abs/1911.08862
代码：https://github.com/alanlukezic/d3s

ROAM: Recurrently Optimizing Tracking Model

论文：https://arxiv.org/abs/1907.12006
代码：https://github.com/skyoung/ROAM

Siam R-CNN: Visual Tracking by Re-Detection

主页：https://www.vision.rwth-aachen.de/page/siamrcnn
论文：https://arxiv.org/abs/1911.12836
论文2：https://www.vision.rwth-aachen.de/media/papers/192/siamrcnn.pdf
代码：https://github.com/VisualComputingInstitute/SiamR-CNN

Cooling-Shrinking Attack: Blinding the Tracker with Imperceptible Noises

论文：https://arxiv.org/abs/2003.09595
代码：https://github.com/MasterBin-IIAU/CSA

High-Performance Long-Term Tracking with Meta-Updater

论文：https://arxiv.org/abs/2004.00305
代码：https://github.com/Daikenan/LTMU

AutoTrack: Towards High-Performance Visual Tracking for UAV with Automatic Spatio-Temporal Regularization

论文：https://arxiv.org/abs/2003.12949
代码：https://github.com/vision4robotics/AutoTrack

Probabilistic Regression for Visual Tracking

论文：https://arxiv.org/abs/2003.12565
代码：https://github.com/visionml/pytracking

MAST: A Memory-Augmented Self-supervised Tracker

论文：https://arxiv.org/abs/2002.07793
代码：https://github.com/zlai0/MAST

Siamese Box Adaptive Network for Visual Tracking

论文：https://arxiv.org/abs/2003.06761
代码：https://github.com/hqucv/siamban

多目标跟踪

3D-ZeF: A 3D Zebrafish Tracking Benchmark Dataset

主页：https://vap.aau.dk/3d-zef/
论文：https://arxiv.org/abs/2006.08466
代码：https://bitbucket.org/aauvap/3d-zef/src/master/
数据集：https://motchallenge.net/data/3D-ZeF20

语义分割

===============================================================

FDA: Fourier Domain Adaptation for Semantic Segmentation

论文：https://arxiv.org/abs/2004.05498
代码：https://github.com/YanchaoYang/FDA

Super-BPD: Super Boundary-to-Pixel Direction for Fast Image Segmentation

论文：暂无
代码：https://github.com/JianqiangWan/Super-BPD

Single-Stage Semantic Segmentation from Image Labels

论文：https://arxiv.org/abs/2005.08104
代码：https://github.com/visinf/1-stage-wseg

Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation

论文：https://arxiv.org/abs/2003.00867
代码：https://github.com/MyeongJin-Kim/Learning-Texture-Invariant-Representation

MSeg: A Composite Dataset for Multi-domain Semantic Segmentation

论文：http://vladlen.info/papers/MSeg.pdf
代码：https://github.com/mseg-dataset/mseg-api

CascadePSP: Toward Class-Agnostic and Very High-Resolution Segmentation via Global and Local Refinement

论文：https://arxiv.org/abs/2005.02551
代码：https://github.com/hkchengrex/CascadePSP

Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision

Oral
论文：https://arxiv.org/abs/2004.07703
代码：https://github.com/feipan664/IntraDA

Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation

论文：https://arxiv.org/abs/2004.04581
代码：https://github.com/YudeWang/SEAM

Temporally Distributed Networks for Fast Video Segmentation

论文：https://arxiv.org/abs/2004.01800
代码：https://github.com/feinanshan/TDNet

Context Prior for Scene Segmentation

论文：https://arxiv.org/abs/2004.01547
代码：https://git.io/ContextPrior

Strip Pooling: Rethinking Spatial Pooling for Scene Parsing

论文：https://arxiv.org/abs/2003.13328
代码：https://github.com/Andrew-Qibin/SPNet

Cars Can’t Fly up in the Sky: Improving Urban-Scene Segmentation via Height-driven Attention Networks

论文：https://arxiv.org/abs/2003.05128
代码：https://github.com/shachoi/HANet

Learning Dynamic Routing for Semantic Segmentation

论文：https://arxiv.org/abs/2003.10401
代码：https://github.com/yanwei-li/DynamicRouting

实例分割

===============================================================

D2Det: Towards High Quality Object Detection and Instance Segmentation

论文：http://openaccess.thecvf.com/content_CVPR_2020/papers/Cao_D2Det_Towards_High_Quality_Object_Detection_and_Instance_Segmentation_CVPR_2020_paper.pdf
代码：https://github.com/JialeCao001/D2Det

PolarMask: Single Shot Instance Segmentation with Polar Representation

论文：https://arxiv.org/abs/1909.13226
代码：https://github.com/xieenze/PolarMask
解读：https://zhuanlan.zhihu.com/p/84890413

CenterMask : Real-Time Anchor-Free Instance Segmentation

论文：https://arxiv.org/abs/1911.06667
代码：https://github.com/youngwanLEE/CenterMask

BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation

论文：https://arxiv.org/abs/2001.00309
代码：https://github.com/aim-uofa/AdelaiDet

Deep Snake for Real-Time Instance Segmentation

论文：https://arxiv.org/abs/2001.01629
代码：https://github.com/zju3dv/snake

Mask Encoding for Single Shot Instance Segmentation

论文：https://arxiv.org/abs/2003.11712
代码：https://github.com/aim-uofa/AdelaiDet

全景分割

===============================================================

Video Panoptic Segmentation

论文：https://arxiv.org/abs/2006.11339
代码：https://github.com/mcahny/vps
数据集：https://www.dropbox.com/s/ecem4kq0fdkver4/cityscapes-vps-dataset-1.0.zip?dl=0

Pixel Consensus Voting for Panoptic Segmentation

论文：https://arxiv.org/abs/2004.01849
代码：还未公布

BANet: Bidirectional Aggregation Network with Occlusion Handling for Panoptic Segmentation

论文：https://arxiv.org/abs/2003.14031

代码：https://github.com/Mooonside/BANet

视频目标分割

=================================================================

A Transductive Approach for Video Object Segmentation

论文：https://arxiv.org/abs/2004.07193
代码：https://github.com/microsoft/transductive-vos.pytorch

State-Aware Tracker for Real-Time Video Object Segmentation

论文：https://arxiv.org/abs/2003.00482
代码：https://github.com/MegviiDetection/video_analyst

Learning Fast and Robust Target Models for Video Object Segmentation

论文：https://arxiv.org/abs/2003.00908
代码：https://github.com/andr345/frtm-vos

Learning Video Object Segmentation from Unlabeled Videos

论文：https://arxiv.org/abs/2003.05020
代码：https://github.com/carrierlxk/MuG

超像素分割

================================================================

Superpixel Segmentation with Fully Convolutional Networks

论文：https://arxiv.org/abs/2003.12929
代码：https://github.com/fuy34/superpixel_fcn

交互式图像分割

==================================================================

Interactive Object Segmentation with Inside-Outside Guidance

论文下载链接：http://openaccess.thecvf.com/content_CVPR_2020/papers/Zhang_Interactive_Object_Segmentation_With_Inside-Outside_Guidance_CVPR_2020_paper.pdf
代码：https://github.com/shiyinzhang/Inside-Outside-Guidance
数据集：https://github.com/shiyinzhang/Pixel-ImageNet

NAS

==============================================================

AOWS: Adaptive and optimal network width search with latency constraints

论文：https://arxiv.org/abs/2005.10481
代码：https://github.com/bermanmaxim/AOWS

Densely Connected Search Space for More Flexible Neural Architecture Search

论文：https://arxiv.org/abs/1906.09607
代码：https://github.com/JaminFong/DenseNAS

MTL-NAS: Task-Agnostic Neural Architecture Search towards General-Purpose Multi-Task Learning

论文：https://arxiv.org/abs/2003.14058
代码：https://github.com/bhpfelix/MTLNAS

FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions

论文下载链接：https://arxiv.org/abs/2004.05565
代码：https://github.com/facebookresearch/mobile-vision

Neural Architecture Search for Lightweight Non-Local Networks

论文：https://arxiv.org/abs/2004.01961
代码：https://github.com/LiYingwei/AutoNL

Rethinking Performance Estimation in Neural Architecture Search

论文：https://arxiv.org/abs/2005.09917
代码：https://github.com/zhengxiawu/rethinking_performance_estimation_in_NAS
解读1：https://www.zhihu.com/question/372070853/answer/1035234510
解读2：https://zhuanlan.zhihu.com/p/111167409

CARS: Continuous Evolution for Efficient Neural Architecture Search

论文：https://arxiv.org/abs/1909.04977
代码（即将开源）：https://github.com/huawei-noah/CARS

GAN

==============================================================

SEAN: Image Synthesis with Semantic Region-Adaptive Normalization

论文：https://arxiv.org/abs/1911.12861
代码：https://github.com/ZPdesu/SEAN

Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation

论文地址：http://openaccess.thecvf.com/content_CVPR_2020/html/Chen_Reusing_Discriminators_for_Encoding_Towards_Unsupervised_Image-to-Image_Translation_CVPR_2020_paper.html
代码地址：https://github.com/alpc91/NICE-GAN-pytorch

Distribution-induced Bidirectional Generative Adversarial Network for Graph Representation Learning

论文：https://arxiv.org/abs/1912.01899
代码：https://github.com/SsGood/DBGAN

PSGAN: Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfer

论文：https://arxiv.org/abs/1909.06956
代码：https://github.com/wtjiang98/PSGAN

Semantically Mutil-modal Image Synthesis

主页：http://seanseattle.github.io/SMIS
论文：https://arxiv.org/abs/2003.12697
代码：https://github.com/Seanseattle/SMIS

Unpaired Portrait Drawing Generation via Asymmetric Cycle Mapping

论文：https://yiranran.github.io/files/CVPR2020_Unpaired%20Portrait%20Drawing%20Generation%20via%20Asymmetric%20Cycle%20Mapping.pdf
代码：https://github.com/yiranran/Unpaired-Portrait-Drawing

Learning to Cartoonize Using White-box Cartoon Representations

论文：https://github.com/SystemErrorWang/White-box-Cartoonization/blob/master/paper/06791.pdf
主页：https://systemerrorwang.github.io/White-box-Cartoonization/
代码：https://github.com/SystemErrorWang/White-box-Cartoonization
解读：https://zhuanlan.zhihu.com/p/117422157
Demo视频：https://www.bilibili.com/video/av56708333

GAN Compression: Efficient Architectures for Interactive Conditional GANs

论文：https://arxiv.org/abs/2003.08936
代码：https://github.com/mit-han-lab/gan-compression

Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral Distributions

论文：https://arxiv.org/abs/2003.01826
代码：https://github.com/cc-hpc-itwm/UpConv

Re-ID

================================================================

High-Order Information Matters: Learning Relation and Topology for Occluded Person Re-Identification

论文：http://openaccess.thecvf.com/content_CVPR_2020/html/Wang_High-Order_Information_Matters_Learning_Relation_and_Topology_for_Occluded_Person_CVPR_2020_paper.html
代码：https://github.com/wangguanan/HOReID

COCAS: A Large-Scale Clothes Changing Person Dataset for Re-identification

论文：https://arxiv.org/abs/2005.07862
数据集：暂无

Transferable, Controllable, and Inconspicuous Adversarial Attacks on Person Re-identification With Deep Mis-Ranking

论文：https://arxiv.org/abs/2004.04199
代码：https://github.com/whj363636/Adversarial-attack-on-Person-ReID-With-Deep-Mis-Ranking

Pose-guided Visible Part Matching for Occluded Person ReID

论文：https://arxiv.org/abs/2004.00230
代码：https://github.com/hh23333/PVPM

Weakly supervised discriminative feature learning with state information for person identification

论文：https://arxiv.org/abs/2002.11939
代码：https://github.com/KovenYu/state-information

3D点云（分类/分割/配准等）

==========================================================================

3D点云卷积

PointASNL: Robust Point Clouds Processing using Nonlocal Neural Networks with Adaptive Sampling

论文：https://arxiv.org/abs/2003.00492
代码：https://github.com/yanx27/PointASNL

Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds

论文下载链接：https://arxiv.org/abs/2003.12971
代码：https://github.com/raoyongming/PointGLR

Grid-GCN for Fast and Scalable Point Cloud Learning

论文：https://arxiv.org/abs/1912.02984
代码：https://github.com/Xharlie/Grid-GCN

FPConv: Learning Local Flattening for Point Convolution

论文：https://arxiv.org/abs/2002.10701
代码：https://github.com/lyqun/FPConv

3D点云分类

PointAugment: an Auto-Augmentation Framework for Point Cloud Classification

论文：https://arxiv.org/abs/2002.10876
代码（即将开源）： https://github.com/liruihui/PointAugment/

3D点云语义分割

RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds

论文：https://arxiv.org/abs/1911.11236
代码：https://github.com/QingyongHu/RandLA-Net
解读：https://zhuanlan.zhihu.com/p/105433460

Weakly Supervised Semantic Point Cloud Segmentation:Towards 10X Fewer Labels

论文：https://arxiv.org/abs/2004.04091
代码：https://github.com/alex-xun-xu/WeakSupPointCloudSeg

PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation

论文：https://arxiv.org/abs/2003.14032
代码：https://github.com/edwardzhou130/PolarSeg

Learning to Segment 3D Point Clouds in 2D Image Space

论文：https://arxiv.org/abs/2003.05593
代码：https://github.com/WPI-VISLab/Learning-to-Segment-3D-Point-Clouds-in-2D-Image-Space

3D点云实例分割

PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation

论文：https://arxiv.org/abs/2004.01658
代码：https://github.com/Jia-Research-Lab/PointGroup

3D点云配准

Feature-metric Registration: A Fast Semi-supervised Approach for Robust Point Cloud Registration without Correspondences

论文：https://arxiv.org/abs/2005.01014
代码：https://github.com/XiaoshuiHuang/fmr

D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features

论文：https://arxiv.org/abs/2003.03164
代码：https://github.com/XuyangBai/D3Feat

RPM-Net: Robust Point Matching using Learned Features

论文：https://arxiv.org/abs/2003.13479
代码：https://github.com/yewzijian/RPMNet

3D点云补全

Cascaded Refinement Network for Point Cloud Completion

论文：https://arxiv.org/abs/2004.03327
代码：https://github.com/xiaogangw/cascaded-point-completion

3D点云目标跟踪

P2B: Point-to-Box Network for 3D Object Tracking in Point Clouds

论文：https://arxiv.org/abs/2005.13888
代码：https://github.com/HaozheQi/P2B

其他

An Efficient PointLSTM for Point Clouds Based Gesture Recognition

论文：http://openaccess.thecvf.com/content_CVPR_2020/html/Min_An_Efficient_PointLSTM_for_Point_Clouds_Based_Gesture_Recognition_CVPR_2020_paper.html
代码：https://github.com/Blueprintf/pointlstm-gesture-recognition-pytorch

人脸

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人脸识别

CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition