DeepLearning-pwcn

There are paper with code and note in terms of deep learning.

• Classification
  • LeNet-5
  • AlexNet
  • NIN(Network In Network)
  • VGG
  • GoogLeNet(Inception-v1)
  • ResNet
  • Inception-v4
  • DenseNet
  • DLA(Deep Layer Aggregation)
  • ShuffleNet
  • MobileNetV3
• Detection
  • One-stage
    • SSD
    • YOLO
    • YOLOv2
    • RetinaNet
    • YOLOv3
    • CornerNet
    • CenterNet
    • YOLOv4
    • YOLOF
  • Two-stage
    • R-CNN
    • SPP
    • Fast R-CNN
    • Faster R-CNN
    • FPN
• Segmentation
  • FCN
  • U-Net
  • Seg-Net
  • DeepLab V1
  • PSPNet
  • DeepLab V2
  • Mask R-CNN
  • DeepLab V3
  • PointNet
  • PointNet++
  • DeepLab V3+
  • DGCNet(Dual GCN)
  • SETR(SEgmentation TRansfomer)
  • Segmenter
  • SegFormer
  • FTN(Fully Transformer Networks)
• Tracking
  • MOT
    • SORT
    • DeepSORT
    • Tracktor
    • FFT(Flow-Fuse Tracker)
    • JRMOT
    • Tracklet
    • DMCT(Deep Multi-Camera Tracking)
    • FairMOT
    • CenterPoint
  • VOT
    • DepthTrack
    • BinocularTrack
    • SiamFC
    • SiamRPN
    • SiamRPN++
    • SiamMask
    • GlobalTrack
    • PAMCC-AOT
    • SiamCAR
    • SiamBAN
    • SiamAttn
    • TSDM
    • SiamGAT
    • RE-SiamNets
• FSS
  • OSLSM
  • co-FCN
  • AMP(Adaptive Masked Proxies)
  • SG-One(Similarity Guidance)
  • CENet(Combinatorial Embedding Network)
  • PANet(Prototype Alignment)
  • CANet(Class Agnostic)
  • PGNet(Pyramid Graph Network)
  • CRNet(Cross-Reference Network)
  • FGN(Fully Guided Network)
  • OTB(On the Texture Bias)
  • LTM(Local Transformation Module)
  • SimPropNet(Similarity Propagation)
  • PPNet(Part-aware Prototype)
  • PFENet(Prior Guided Feature Enrichment Network)
  • PMMs(Prototype Mixture Models)
  • GFS-Seg(Generalized Few-Shot)
  • SCL(Self-Corss Learning)
  • ASGNet(Adaptive Superpixel-guided Network)
  • HSNet(Hypercorrelation Squeeze)
  • BAM
• 3D-Face
  • 3DMM
  • CameraCalibration
  • Bilinear
  • DDE
  • FaceWarehouse
  • Face2Face
  • DynamicAvatars
  • FLAME
  • Nonlinear
  • DynamicRigidityPrior
  • Deep3D
  • SimpleAnimation
  • RingNet
  • FOCUS
  • MICA
  • HRN
• Attention
  • Transformer
  • Non-local
  • Image Transformer
  • ViT(Vision Transformer)
  • Swin Transformer
  • ResT
  • DS-Net(Dual Stream Network)
  • TransCNN
  • Shuffle Transformer
• RGBD-SOT
  • UC-Net
  • JL-DCF(Joint Learning and Densely-Cooperative Fusion)
  • SA-Gate(Separation-and-Aggregation Gate)
  • BiANet(Bilateral Attention Network)
  • DSA^2F(Depth-Sensitive Attention and Automatic Multi-Modal Fusion)
• Unsupervised
  • SimSiam
• Detection-3D
  • PV-RCNN
• FSL
  • RN(Relation Network)
• GAN
  • GAN
  • BeautyGAN
• Optimization
  • ReLU
  • Momentum
  • Dropout
  • Adam
  • BN
  • GDoptimization
• Survey
  • 3D-Detection-Survey-2019
  • FSL-Survey-2019
  • MOT-Survey-2020
  • Transformer-Survey-2021

Image Classification

Title	Paper	Conf	Code
LeNet-5	Gradient-based learning applied to document recognition	IEEE(1998)	[code]
AlexNet	ImageNet Classification with Deep Convolutional Neural Networks	NIPS(2012)	[code]
NIN	Network In Network	arXiv(2013)	PyTorch
VGG	Very Deep Convolutional Networks for Large-Scale Image Recognition	ICLR(2015)	[code]
GoogLeNet	Going deeper with convolutions	CVPR(2015)	PyTorch
ResNet	Deep Residual Learning for Image Recognition	CVPR(2016)	PyTorch
Inception-v4	Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning	AAAI(2017)	[code]
DenseNet	Densely Connected Convolutional Networks	CVPR(2017)	[code]
DLA	Deep Layer Aggregation	CVPR(2018)	PyTorch
ShuffleNet	ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices	CVPR(2018)	[code]
MobileNetV3	Searching for MobileNetV3	ICCV(2019)	[code]

More information can be found in Awesome - Image Classification.

Object Detection

Title	Paper	Conf	Code
R-CNN	Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation	CVPR(2014)	[code]
SPP	Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition	TPAMI(2015)	[code]
Fast R-CNN	Fast R-CNN	ICCV(2015)	[code]
Faster R-CNN	Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks	NIPS(2015)	PyTorch
SSD	SSD: Single Shot MultiBox Detector	ECCV(2016)	Caffe
YOLO	You Only Look Once: Unified, Real-Time Object Detection	CVPR(2016)	[code]
YOLOv2	YOLO9000: Better, Faster, Stronger	CVPR(2017)	[code]
FPN	Feature Pyramid Networks for Object Detection	CVPR(2017)	[code]
RetinaNet	Focal Loss for Dense Object Detection	ICCV(2017)	[code]
YOLOv3	YOLOv3: An Incremental Improvement	arXiv(2018)	Offical
CornerNet	CornerNet: Detecting Objects as Paired Keypoints	ECCV(2018)	PyTorch
CenterNet	Objects as Points	arXiv(2019)	PyTorch
YOLOv4	YOLOv4: Optimal Speed and Accuracy of Object Detection	arXiv(2020)	Offical
YOLOF	You Only Look One-level Feature	CVPR(2021)	PyTorch

More information can be found in awesome-object-detection.

Object Segmentation

Title	Paper	Conf	Code
FCN	Fully convolutional networks for semantic segmentation	CVPR(2015)	PyTorch
U-Net	U-Net: Convolutional Networks for Biomedical Image Segmentation	MICCAI(2015)	PyTorch
Seg-Net	SegNet: A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling	arXiv(2015)	PyTorch
DeepLab V1	Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs	arXiv(2014) / ICLR(2015)	PyTorch
PSPNet	Pyramid Scene Parsing Network	CVPR(2017)	PyTorch
DeepLab V2	DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs	arXiv(2016) / TPAMI(2017)	PyTorch
Mask R-CNN	Mask R-CNN	ICCV / TPAMI(2017)	PyTorch
DeepLab V3	Rethinking Atrous Convolution for Semantic Image Segmentation	arXiv(2017)	PyTorch
PointNet	PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation	CVPR(2017)	PyTorch
PointNet++	PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space	NIPS(2017)	PyTorch
DeepLab V3+	Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation	ECCV(2018)	PyTorch
DGCNet	Dual Graph Convolutional Network for Semantic Segmentation	BMVC(2019)	PyTorch
SETR	Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers	CVPR(2021)	PyTorch
Segmenter	Segmenter: Transformer for Semantic Segmentation	arXiv(2021)	PyTorch
SegFormer	SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers	arXiv(2021)	PyTorch
FTN	Fully Transformer Networks for Semantic ImageSegmentation	arXiv(2021)	[code]

Object Tracking

Title	Paper	Conf	Code
SORT	Simple Online and Realtime Tracking	ICIP(2016)	PyTorch
DepthTrack	Real-time depth-based tracking using a binocular camera	WCICA(2016)	[code]
DeepSORT	Simple Online and Realtime Tracking with a Deep Association Metric	ICIP(2017)	PyTorch
BinocularTrack	Research on Target Tracking Algorithm Based on Parallel Binocular Camera	ITAIC(2019)	[code]
SiamFC	Fully-Convolutional Siamese Networks for Object Tracking	ECCV(2016)	PyTorch
SiamRPN	High Performance Visual Tracking with Siamese Region Proposal Network	CVPR(2018)	PyTorch
SiamRPN++	SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networks	CVPR(2019)	PyTorch
SiamMask	Fast Online Object Tracking and Segmentation: A Unifying Approach	CVPR(2019)	PyTorch
Tracktor	Tracking without bells and whistles	ICCV(2019)	PyTorch
GlobalTrack	GlobalTrack: A Simple and Strong Baseline for Long-term Tracking	AAAI(2020)	PyTorch
SiamCAR	SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking	CVPR(2020)	PyTorch
SiamBAN	Siamese Box Adaptive Network for Visual Tracking	CVPR(2020)	PyTorch
SiamAttn	Deformable Siamese Attention Networks for Visual Object Tracking	CVPR(2020)	PyTorch
PAMCC-AOT	Pose-Assisted Multi-Camera Collaboration for Active Object Tracking	AAAI(2020)	[code]
FFT	Multiple Object Tracking by Flowing and Fusing	arXiv(2020)	[code]
JRMOT	JRMOT: A Real-Time 3D Multi-Object Tracker and a New Large-Scale Dataset	arXiv(2020)	[code]
Tracklet	Multi-object Tracking via End-to-end Tracklet Searching and Ranking	arXiv(2020)	[code]
DMCT	Real-time 3D Deep Multi-Camera Tracking	arXiv(2020)	[code]
FairMOT	A Simple Baseline for Multi-Object Tracking	arXiv(2020)	PyTorch
TSDM	TSDM: Tracking by SiamRPN++ with a Depth-refiner and a Mask-generator	arXiv(2020)	PyTorch
CenterPoint	Center-based 3D Object Detection and Tracking	CVPR(2021)	PyTorch
SiamGAT	Graph Attention Tracking	CVPR(2021)	PyTorch
RE-SiamNets	Rotation Equivariant Siamese Networks for Tracking	CVPR(2021)	PyTorch

Few-Shot Segmentation

Title	Paper	Conf	Code
OSLSM	One-Shot Learning for Semantic Segmentation	BMVC(2017)	Caffe
co-FCN	Conditional Networks for Few-Shot Semantic Segmentation	ICLR(2018)	[code]
AMP	AMP: Adaptive Masked Proxies for Few-Shot Segmentation	ICCV(2019)	Pytorch
SG-One	SG-One: Similarity Guidance Network for One-Shot Semantic Segmentation	arXiv(2018) / TCYB(2020)	PyTorch
CENet	Learning Combinatorial Embedding Networks for Deep Graph Matching	ICCV(2019)	Pytorch
PANet	PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment	ICCV(2019)	PyTorch
CANet	CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learning	CVPR(2019)	PyTorch
PGNet	Pyramid Graph Networks with Connection Attentions for Region-Based One-Shot Semantic Segmentation	ICCV(2019)	[code]
CRNet	CRNet: Cross-Reference Networks for Few-Shot Segmentation	CVPR(2020)	[code]
FGN	FGN: Fully Guided Network for Few-Shot Instance Segmentation	CVPR(2020)	[code]
OTB	On the Texture Bias for Few-Shot CNN Segmentation	arXiv(2020)	TensorFlow
LTM	A New Local Transformation Module for Few-Shot Segmentation	MMMM(2020)	[code]
SimPropNet	SimPropNet: Improved Similarity Propagation for Few-shot Image Segmentation	IJCAI(2020)	[code]
PPNet	Part-aware Prototype Network for Few-shot Semantic Segmentation	ECCV(2020)	PyTorch
PFENet	PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation	TPAMI(2020)	PyTorch
PMMs	Prototype Mixture Models for Few-shot Semantic Segmentation	ECCV(2020)	PyTorch
GFS-Seg	Generalized Few-Shot Semantic Segmentation	arXiv(2020)	[code]
SCL	Self-Guided and Cross-Guided Learning for Few-Shot Segmentation	CVPR(2021)	PyTorch
ASGNet	Adaptive Prototype Learning and Allocation for Few-Shot Segmentation	CVPR(2021)	PyTorch
HSNet	Hypercorrelation Squeeze for Few-Shot Segmenation	ICCV(2021)	PyTorch
BAM	Learning What Not to Segment: A New Perspective on Few-Shot Segmentation	CVPR(2022)	PyTorch

More information can be found in Few-Shot-Semantic-Segmentation-Papers.

3D Face Reconstruction and Facial Animation

Title	Paper	Conf	Code
3DMM	A Morphable Model For The Synthesis Of 3D Faces	SIGGRAPH(1999)	[code]
CameraCalibration	A Flexible New Technique for CameraCalibration	TPAMI(2000)	[code]
Bilinear	Bilinear Models for 3-D Face andFacial Expression Recognition	TIFS(2008)	[code]
DDE	Displaced Dynamic Expression Regression forReal-time Facial Tracking and Animation	TOG(2014)	[code]
FaceWarehouse	FaceWarehouse: a 3D Facial Expression Databasefor Visual Computing	TVCG(2014)	[code]
Face2Face	Face2Face: Real-Time Face Capture and Reenactment of RGB Videos	CVPR(2016)	[code]
DynamicAvatars	Real-time Facial Animation with Image-based Dynamic Avatars	TOG(2016)	[code]
FLAME	Learning a model of facial shape and expression from 4D scans	TOG(2017)	Tensorflow PyTorch
Nonlinear	Nonlinear 3D Face Morphable Model	CVPR(2018)	Tensorflow
DynamicRigidityPrior	Stabilized real-time face tracking via a learned dynamic rigidity prior	TOG(2018)	[code]
Deep3D	Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set	CVPR(2019)	Tensorflow PyTorch
SimpleAnimation	Face It!: A Pipeline for Real-Time Performance-Driven Facial Animation	ICIP(2019)	[code]
RingNet	Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision	CVPR(2019)	Tensorflow
FOCUS	To fit or not to fit: Model-based Face Reconstruction and Occlusion Segmentation from Weak Supervision	arXiv(2021)	PyTorch
MICA	Towards Metrical Reconstruction of Human Faces	ECCV(2022)	PyTorch
HRN	A Hierarchical Representation Network for Accurate and Detailed Face Reconstruction from In-The-Wild Images	CVPR(2023)	PyTorch

Attention or Transformer

Title	Paper	Conf	Code
Transformer	Attention Is All You Need	arXiv(2017)	TensorFlow
Non-local	Non-local Neural Networks	CVPR(2018)	PyTorch
Image Transformer	Image Transformer	arXiv(2018)	[code]
ViT	An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale	arXiv(2020)	PyTorch
Swin Transformer	Swin Transformer: Hierarchical Vision Transformer using Shifted Windows	arXiv(2021)	PyTorch
ResT	ResT: An Efficient Transformer for Visual Recognition	arXiv(2021)	PyTorch
DS-Net	Dual-stream Network for Visual Recognition	arXiv(2021)	[code]
TransCNN	Transformer in Convolutional Neural Networks	arXiv(2021)	PyTorch
Shuffle Transformer	Shuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer	arXiv(2021)	PyTorch

Salient Object Detection

Title	Paper	Conf	Code
UC-Net	UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders	CVPR(2020)	PyTorch
JL-DCF	JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection	CVPR(2020)	PyTorch
SA-Gate	Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation	ECCV(2020)	PyTorch
BiANet	Bilateral Attention Network for RGB-D Salient Object Detection	TIP(2021)	[Code]
DSA^2F	Deep RGB-D Saliency Detection with Depth-Sensitive Attention and Automatic Multi-Modal Fusion	CVPR(2021)	[Code]

Unsupervised Learning

Title	Paper	Conf	Code
SimSiam	Exploring Simple Siamese Representation Learning	CVPR(2021)	PyTorch

3D Object Detection

Title	Paper	Conf	Code
PV-RCNN	PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection	CVPR(2020)	PyTorch

Few-Shot Learning

Title	Paper	Conf	Code
RN	Learning to Compare: Relation Network for Few-Shot Learning	CVPR(2018)	PyTorch

Generative Adversarial Network

Title	Paper	Conf	Code
GAN	Generative Adversarial Networks	arXiv(2014)	[code]
BeautyGAN	BeautyGAN: Instance-level Facial Makeup Transfer with Deep Generative Adversarial Network	ACM MM(2018)	TensorFlow

Optimization

Title	Paper	Conf	Code
ReLU	Deep Sparse Rectifier Neural Networks	JMLR(2011)	[code]
Momentum	On the importance of initialization and momentum in deep learning	ICML(2013)	[code]
Dropout	Dropout: a simple way to prevent neural networks from overfitting	JMLR(2014)	[code]
Adam	Adam: A Method for Stochastic Optimization	ICLR(2015)	[code]
BN	Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift	ICML(2015)	[code]
GDoptimization	An overview of gradient descent optimization algorithms	arXiv(2016)	[code]

Survey

Title	Paper	Conf
3D-Detection-Survey-2019	A Survey on 3D Object Detection Methods for Autonomous Driving Applications	ITS(2019)
FSL-Survey-2019	Generalizing from a Few Examples: A Survey on Few-Shot Learning	CSUR(2019)
MOT-Survey-2020	Deep Learning in Video Multi-Object Tracking: A Survey	Neurocomputing(2020)
Transformer-Survey-2021	A Survey of Transformers	arXiv(2021)