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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

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

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

人脸识别


CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition

  • 论文:https://arxiv.org/abs/2004.00288

  • 代码:https://github.com/HuangYG123/CurricularFace

Learning Meta Face Recognition in Unseen Domains

  • 论文:https://arxiv.org/abs/2003.07733

  • 代码:https://github.com/cleardusk/MFR

  • 解读:https://mp.weixin.qq.com/s/YZoEnjpnlvb90qSI3xdJqQ

人脸检测


人脸活体检测


Searching Central Difference Convolutional Networks for Face Anti-Spoofing

  • 论文:https://arxiv.org/abs/2003.04092

  • 代码:https://github.com/ZitongYu/CDCN

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