- Papers
- Scene Recognition / Scene Classification
- Blogs
分类、识别论文与项目
Papers
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
- auothor: Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, Trevor Darrell
- arxiv: http://arxiv.org/abs/1310.1531
CNN Features off-the-shelf: an Astounding Baseline for Recognition
- intro: CVPR 2014
- arxiv: http://arxiv.org/abs/1403.6382
HD-CNN: Hierarchical Deep Convolutional Neural Network for Image Classification
HD-CNN: Hierarchical Deep Convolutional Neural Network for Large Scale Visual Recognition
- intro: ICCV 2015
- intro: introduce hierarchical deep CNNs (HD-CNNs) by embedding deep CNNs into a category hierarchy
- project page: https://sites.google.com/site/homepagezhichengyan/home/hdcnn
- arxiv: https://arxiv.org/abs/1410.0736
- code: https://sites.google.com/site/homepagezhichengyan/home/hdcnn/code
- github: https://github.com/stephenyan1231/caffe-public/tree/hdcnn
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
- intro: ImageNet top-5 error: 4.94%
- arxiv: http://arxiv.org/abs/1502.01852
- notes: http://blog.csdn.net/happynear/article/details/45440811
Humans and deep networks largely agree on which kinds of variation make object recognition harder
- arxiv: http://arxiv.org/abs/1604.06486
- review: https://www.technologyreview.com/s/601387/why-machine-vision-is-flawed-in-the-same-way-as-human-vision/
FusionNet: 3D Object Classification Using Multiple Data Representations
From image recognition to object recognition
Deep FisherNet for Object Classification
Hyperspectral CNN Classification with Limited Training Samples
The More You Know: Using Knowledge Graphs for Image Classification
- intro: CMU. GSNN
- arxiv: https://arxiv.org/abs/1612.04844
MaxMin Convolutional Neural Networks for Image Classification
- paper: http://webia.lip6.fr/~thomen/papers/Blot_ICIP_2016.pdf
- github: https://github.com/karandesai-96/maxmin-cnn
Cost-Effective Active Learning for Deep Image Classification
- intro: TCSVT 2016. Sun Yat-sen University & Guangzhou University
- arxiv: https://arxiv.org/abs/1701.03551
Deep Collaborative Learning for Visual Recognition
https://www.arxiv.org/abs/1703.01229
Convolutional Low-Resolution Fine-Grained Classification
https://arxiv.org/abs/1703.05393
Multi-object Recognition
Multiple Object Recognition with Visual Attention
- keyword: deep recurrent neural network, reinforcement learning
- arxiv: https://arxiv.org/abs/1412.7755
- github: https://github.com/jrbtaylor/visual-attention
Multiple Instance Learning Convolutional Neural Networks for Object Recognition
- intro: ICPR 2016 Oral
- arxiv: https://arxiv.org/abs/1610.03155
Face Recognition
DeepID
Deep Learning Face Representation from Predicting 10,000 Classes
- intro: CVPR 2014
- paper: http://mmlab.ie.cuhk.edu.hk/pdf/YiSun_CVPR14.pdf
- github: https://github.com/stdcoutzyx/DeepID_FaceClassify
DeepID2
Deep Learning Face Representation by Joint Identification-Verification
- paper: http://papers.nips.cc/paper/5416-analog-memories-in-a-balanced-rate-based-network-of-e-i-neurons
基于Caffe的DeepID2实现
DeepID2+
Deeply learned face representations are sparse, selective, and robust
- arxiv: http://arxiv.org/abs/1412.1265
- video: http://research.microsoft.com/apps/video/?id=260023
- mirror: http://pan.baidu.com/s/1boufl3x
DeepFace
DeepFace: Closing the Gap to Human-Level Performance in Face Verification
- paper: https://www.cs.toronto.edu/~ranzato/publications/taigman_cvpr14.pdf
- slides: http://valse.mmcheng.net/ftp/20141126/MingYang.pdf
- github: https://github.com/RiweiChen/DeepFace
Deep Face Recognition
- intro: BMVC 2015
- paper: http://www.robots.ox.ac.uk/~vgg/publications/2015/Parkhi15/parkhi15.pdf
- homepage: http://www.robots.ox.ac.uk/~vgg/software/vgg_face/
- github(Keras): https://github.com/rcmalli/keras-vggface
FaceNet
FaceNet: A Unified Embedding for Face Recognition and Clustering
- intro: Google. CVPR 2015
- arxiv: http://arxiv.org/abs/1503.03832
- github(Tensorflow): https://github.com/davidsandberg/facenet
- github(Caffe): https://github.com/hizhangp/triplet
Targeting Ultimate Accuracy: Face Recognition via Deep Embedding
- intro: CVPR 2015
- arxiv: http://arxiv.org/abs/1506.07310
Learning Robust Deep Face Representation
A Light CNN for Deep Face Representation with Noisy Labels
- arxiv: https://arxiv.org/abs/1511.02683
- github: https://github.com/AlfredXiangWu/face_verification_experiment
Pose-Aware Face Recognition in the Wild
Triplet Probabilistic Embedding for Face Verification and Clustering
- intro: Oral Paper in BTAS 2016; NVIDIA Best paper Award
- arxiv: https://arxiv.org/abs/1604.05417
- github(Keras): https://github.com/meownoid/face-identification-tpe
Recurrent Regression for Face Recognition
A Discriminative Feature Learning Approach for Deep Face Recognition
- intro: ECCV 2016
- intro: center loss
- paper: http://ydwen.github.io/papers/WenECCV16.pdf
- github: https://github.com/ydwen/caffe-face
- github: https://github.com/pangyupo/mxnet_center_loss
How Image Degradations Affect Deep CNN-based Face Recognition?
VIPLFaceNet / SeetaFace Engine
VIPLFaceNet: An Open Source Deep Face Recognition SDK
SeetaFace Engine
- intro: SeetaFace Engine is an open source C++ face recognition engine, which can run on CPU with no third-party dependence.
- github: https://github.com/seetaface/SeetaFaceEngine
A Discriminative Feature Learning Approach for Deep Face Recognition
- intro: ECCV 2016
- paper: http://ydwen.github.io/papers/WenECCV16.pdf
Sparsifying Neural Network Connections for Face Recognition
Range Loss for Deep Face Recognition with Long-tail
Hybrid Deep Learning for Face Verification
- intro: TPAMI 2016. CNN+RBM
- paper: http://www.ee.cuhk.edu.hk/~xgwang/papers/sunWTpami16.pdf
Towards End-to-End Face Recognition through Alignment Learning
- intro: Tsinghua University
- arxiv: https://arxiv.org/abs/1701.07174
Multi-Task Convolutional Neural Network for Face Recognition
NormFace: L2 Hypersphere Embedding for Face Verification
SphereFace: Deep Hypersphere Embedding for Face Recognition
- intro: CVPR 2017
- arxiv: http://wyliu.com/papers/LiuCVPR17.pdf
L2-constrained Softmax Loss for Discriminative Face Verification
https://arxiv.org/abs/1703.09507
Video Face Recognition
Attention-Set based Metric Learning for Video Face Recognition
https://arxiv.org/abs/1704.03805
Projects
Using MXNet for Face-related Algorithm
clmtrackr: Javascript library for precise tracking of facial features via Constrained Local Models
- github: https://github.com/auduno/clmtrackr
- blog: http://auduno.com/post/61888277175/fitting-faces
- demo: http://auduno.github.io/clmtrackr/examples/facesubstitution.html
- demo: http://auduno.github.io/clmtrackr/face_deformation_video.html
- demo: http://auduno.github.io/clmtrackr/examples/clm_emotiondetection.html
- demo: http://auduno.com/post/84214587523/twisting-faces
DeepLogo
- intro: A brand logo recognition system using deep convolutional neural networks.
- github: https://github.com/satojkovic/DeepLogo
Deep-Leafsnap
- intro: LeafSnap replicated using deep neural networks to test accuracy compared to traditional computer vision methods.
- github: https://github.com/sujithv28/Deep-Leafsnap
OpenFace
OpenFace: Face Recognition with Deep Neural Networks
- homepage: http://cmusatyalab.github.io/openface/
- github: https://github.com/cmusatyalab/openface
- github: https://github.com/aybassiouny/OpenFaceCpp
OpenFace 0.2.0: Higher accuracy and halved execution time
OpenFace: A general-purpose face recognition library with mobile applications
FaceVerification: An Experimental Implementation of Face Verification, 96.8% on LFW
OpenFace: an open source facial behavior analysis toolkit
- intro: a state-of-the art open source tool intended for facial landmark detection, head pose estimation, facial action unit recognition, and eye-gaze estimation.
- github: https://github.com/TadasBaltrusaitis/OpenFace
Resources
Face-Resources
Fine-grained Recognition
Bilinear CNN Models for Fine-grained Visual Recognition
- intro: ICCV 2015
- homepage: http://vis-www.cs.umass.edu/bcnn/
- paper: http://vis-www.cs.umass.edu/bcnn/docs/bcnn_iccv15.pdf
- arxiv: http://arxiv.org/abs/1504.07889
- bitbucket: https://bitbucket.org/tsungyu/bcnn.git
Fine-grained Image Classification by Exploring Bipartite-Graph Labels
- intro: CVPR 2016
- project page: http://www.f-zhou.com/fg.html
- arxiv: http://arxiv.org/abs/1512.02665
- demo: http://www.f-zhou.com/fg_demo/
Embedding Label Structures for Fine-Grained Feature Representation
- intro: CVPR 2016
- arxiv: http://arxiv.org/abs/1512.02895
- paper: http://webpages.uncc.edu/~szhang16/paper/CVPR16_structured_labels.pdf
Fine-grained Categorization and Dataset Bootstrapping using Deep Metric Learning with Humans in the Loop
Fully Convolutional Attention Localization Networks: Efficient Attention Localization for Fine-Grained Recognition
Localizing by Describing: Attribute-Guided Attention Localization for Fine-Grained Recognition
Learning Deep Representations of Fine-grained Visual Descriptions
- intro: CVPR 2016
- arxiv: http://arxiv.org/abs/1605.05395
- github: https://github.com/reedscot/cvpr2016
IDNet: Smartphone-based Gait Recognition with Convolutional Neural Networks
Picking Deep Filter Responses for Fine-grained Image Recognition
- intro: CVPR 2016
SPDA-CNN: Unifying Semantic Part Detection and Abstraction for Fine-grained Recognition
- intro: CVPR 2016
Part-Stacked CNN for Fine-Grained Visual Categorization
- intro: CVPR 2016
Fine-grained Recognition in the Noisy Wild: Sensitivity Analysis of Convolutional Neural Networks Approaches
- intro: BMVC 2016
- arxiv: https://arxiv.org/abs/1610.06756
Low-rank Bilinear Pooling for Fine-Grained Classification
- intro: CVPR 2017
- project page: http://www.ics.uci.edu/~skong2/lr_bilinear.html
- arxiv: https://arxiv.org/abs/1611.05109
- github: https://github.com/aimerykong/Low-Rank-Bilinear-Pooling
细粒度图像分析
- intro: by 吴建鑫, NJU. VALSE 2017 Annual Progress Review Series
- slides: http://mac.xmu.edu.cn/valse2017/ppt/APR/wjx_APR.pdf
Food Recognition
DeepFood: Deep Learning-Based Food Image Recognition for Computer-Aided Dietary Assessment
Im2Calories: towards an automated mobile vision food diary
- intro: recognize the contents of your meal from a single image, then predict its nutritional contents, such as calories
- paper: http://www.cs.ubc.ca/~murphyk/Papers/im2calories_iccv15.pdf
Food Image Recognition by Using Convolutional Neural Networks (CNNs)
Wide-Slice Residual Networks for Food Recognition
Food Classification with Deep Learning in Keras / Tensorflow
- blog: http://blog.stratospark.com/deep-learning-applied-food-classification-deep-learning-keras.html
- github: https://github.com/stratospark/food-101-keras
ChineseFoodNet: A large-scale Image Dataset for Chinese Food Recognition
https://arxiv.org/abs/1705.02743
Instrument Recognition
Automatic Instrument Recognition in Polyphonic Music Using Convolutional Neural Networks
Musical Instrument Recognition
Deep Convolutional Networks on the Pitch Spiral for Musical Instrument Recognition
- paper: https://github.com/lostanlen/ismir2016/blob/master/paper/lostanlen_ismir2016.pdf
- github: https://github.com/lostanlen/ismir2016
Clothes Recognition
DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations
- intro: CVPR 2016. FashionNet
- project page: http://personal.ie.cuhk.edu.hk/~lz013/projects/DeepFashion.html
- paper: http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Liu_DeepFashion_Powering_Robust_CVPR_2016_paper.pdf
Multi-Task Curriculum Transfer Deep Learning of Clothing Attributes
Star-galaxy Classification
Star-galaxy Classification Using Deep Convolutional Neural Networks
- intro: MNRAS
- arxiv: http://arxiv.org/abs/1608.04369
- github: https://github.com/EdwardJKim/dl4astro
Logo Recognition
Deep Learning for Logo Recognition
Scene Recognition / Scene Classification
Learning Deep Features for Scene Recognition using Places Database
- paper: http://places.csail.mit.edu/places_NIPS14.pdf
- gihtub: https://github.com/metalbubble/places365
Using neon for Scene Recognition: Mini-Places2
- intro: This is an implementation of the deep residual network used for Mini-Places2 as described in He et. al., “Deep Residual Learning for Image Recognition”.
- blog: http://www.nervanasys.com/using-neon-for-scene-recognition-mini-places2/
- github: https://github.com/hunterlang/mpmz
Scene Classification with Inception-7
Semantic Clustering for Robust Fine-Grained Scene Recognition
Places: An Image Database for Deep Scene Understanding
- project page: http://places.csail.mit.edu/index.html
- arxiv: https://arxiv.org/abs/1610.02055
Leaderboard
Leaderboard of Places Database
- intro: currently rank1: Qian Zhang(Beijing Samsung Telecom R&D Center), 0.6410@top1, 0.9065@top5
- homepage: http://places.csail.mit.edu/user/leaderboard.php
Blogs
What is the class of this image ? - Discover the current state of the art in objects classification
- intro: “Discover the current state of the art in objects classification.”
- intro: MNIST, CIFAR-10, CIFAR-100, STL-10, SVHN, ILSVRC2012 task 1
- blog: http://rodrigob.github.io/are_we_there_yet/build/classification_datasets_results.html
Object Recognition with Convolutional Neural Networks in the Keras Deep Learning Library
The Effect of Resolution on Deep Neural Network Image Classification Accuracy