DailyReadPaper

Academic Alchemy Furnace, beginning from 18th Jan 2019.

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Here is the content of our project.

• 2019-01-18:{9}

  1. Salient Object Detection via High-to-Low Hierarchical Context Aggregation
     1. arXiv:1812.10956 (Submitted on 28 Dec 2018)
  2. [16]Deeply Supervised Salient Object Detection with Short Connections
     1. CVPR 2017
  3. [55]Amulet: Aggregating multi-level convolutional features for salient object detection
     1. ICCV 2017
  4. [44]Detect globally, refine locally: A novel approach to saliency detection
     1. CVPR 2018
  5. [58]Pyramid scene parsing network
     1. CVPR 2017
  6. [52]Context Encoding for Semantic Segmentation
     1. CVPR 2018
  7. [4]Progressive Attention Guided Recurrent Network for Salient Object Detection
     1. CVPR 2018
  8. [57]Reverse Attention for Salient Object Detection
     1. ECCV 2018
  9. [51]Learning to Promote Saliency Detectors
     1. CVPR 2018

• 2019-01-19:{4}

  1. Optimal Fine Grained Retrieval via Decorrelated Centralized Loss with Normalize-Scale layer
     1. AAAI 2019
  2. Hypergraph Neural Networks
     1. AAAI 2019
  3. Learning Neural Bag-of-Matrix-Summarization with Riemannian Network
     1. AAAI 2019
  4. A Riemannian Network for SPD Matrix Learning
     1. AAAI 2017
     2. This is a reference in [3], namely Learning Neural Bag-of-Matrix-Summarization with Riemannian Network.

• 2019-01-20:{6}

  1. Group normalization
     1. ECCV 2018
  2. Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization
     1. CVPR 2018
  3. RIEMANNIAN ADAPTIVE OPTIMIZATION METHODS
     1. ICLR 2019 (open review)
  4. Decorrelated Batch Normalization
     1. CVPR 2018
  5. Orthogonal weight normalization: Solution to optimization over multiple dependent stiefel manifolds in deep neural networks
     1. AAAI 2018
  6. Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
     1. ECCV 2018

• 2019-01-21:{7}

  1. Dissimilarity Representation Learning for Generalized Zero-Shot Recognition
     1. ACM MM 2018
  2. A rethink about A Riemannian Network for SPD Matrix Learning
     1. By myself
  3. Covariance Discriminative Learning: A Natural and Efficient Approach to Image Set Classification
     1. CVPR 2012
     2. Wang, Ruiping and Guo, Huimin and Davis, Larry S and Dai, Qionghai
  4. Second-order Convolutional Neural Networks
     1. Clinical Immunology & Immunopathology
  5. Covariance Pooling for Facial Expression Recognition
     1. arXiv preprint arXiv:1805.04855
  6. Building Deep Networks on Grassmann Manifolds
     1. AAAI 2018
  7. Deep Learning on Lie Groups for Skeleton-based Action Recognition
     1. CVPR 2017 spotlight

• 2019-01-22:{3}

  1. BAM: Convolutional Block Attention Module
     1. ECCV 2018
  2. Learning with rethinking: Recurrently improving convolutional neural networks through feedback
     1. PR 2018
  3. Look closer to see better: Recurrent attention convolutional neural network for fine-grained image recognition
     1. CVPR 2017

• 2019-01-23:{2}

  1. A rethink for Learning Neural Bag-of-Matrix-Summarization with Riemannian Network

  2. Stochastic neighbor compression

     1. ICML 2014

• 2019-01-24:{6}

  1. Towards Optimal Fine Grained Retrieval via Decorrelated Centralized Loss with Normalize-Scale layer
     1. AAAI 2019
  2. Person re-identification by deep joint learning of multi-loss classification
     1. IJCAI 2017
  3. Support Vector Guided Softmax Loss for Face Recognition
     1. arXiv preprint arXiv:1812.11317
  4. Deep Face Recognition: A Survey
     1. CVPR 2019
  5. Ring loss: Convex Feature Normalization for Face Recognition
     1. CVPR 2018
  6. Deep feature embedding learning for person re-identification using lifted structured loss
     1. ICASSP 2018

• 2019-01-25:{3}

  1. Global Second-order Pooling Convolutional Networks
     1. Arxiv 2018
  2. Is second-order information helpful for large-scale visual recognition},
     1. ICCV 2017
  3. Statistically Motivated Second Order Pooling
     1. ECCV 2018

• 2019-01-26:{2}

  1. Grad-cam: Visual explanations from deep networks via gradient-based localization
     1. ICCV 2017
  2. PAYING MORE ATTENTION TO ATTENTION： IMPROVING THE PERFORMANCE OF CONVOLUTIONAL NEURAL NETWORKS VIA ATTENTION TRANSFER
     1. ICLR 2017

• 2019-01-27:{7}

  1. Pedestrian Attribute Recognition: A Survey
     1. Arxiv 2019
  2. Anomaly Detection in Road Traffic Using Visual Surveillance: A Survey
     1. Arxiv 2019
  3. A Short Survey on Probabilistic Reinforcement Learning
     1. Arxiv 2019
  4. A Survey of the Recent Architectures of Deep Convolutional Neural Networks
     1. Arxiv 2019
  5. ptimization Models for Machine Learning: A Survey
     1. Arxiv 2019
  6. Deep Learning for Anomaly Detection: A Survey
     1. Arxiv 2019
  7. A Comprehensive Survey on Graph Neural Networks
     1. Arxiv 2019

• 2019-01-28:{4}

  1. Revisiting Self-Supervised Visual Representation Learning
     1. Arxiv 2019
     2. Google Brain
  2. Deep Multimodality Model for Multi-task Multi-view Learning
     1. Arxiv 2019
     2. Microsoft AI & Research
  3. One-Class Convolutional Neural Network
     1. Arxiv 2019
     2. github.com/otkupjnoz/oc-cnn.
     3. Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA. This work was supported by the NSF grant 1801435.
  4. In Defense of the Triplet Loss for Visual Recognition
     1. Arxiv 2019
     2. Honda Research

• 2019-01-29:{4}

  1. SVDNet for Pedestrian Retrieval
     1. ICCV 2017
  2. Reducing overfitting in deep networks by decorrelating representations
     1. ICLR 2016
  3. All you need is beyond a good init: Exploring better solution for training extremely deep convolutional neural networks with orthonormality and modulation
     1. CVPR 2017
  4. Learning deep architectures via generalized whitened neural networks
     1. ICML 2017

• 2019-01-30:{4}

  1. A rethink about All you need is beyond a good init: Exploring better solution for training extremely deep convolutional neural networks with orthonormality and modulation
     1. http://www.erogol.com/need-good-init/
  2. [30]Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
     1. Andrew M. Saxe (asaxe@stanford.edu)
  3. ALL YOU NEED IS A GOOD INIT
     1. Center for Machine Perception
  4. [32]Understanding and improving convolutional neural networks via concatenated rectified linear units
     1. ICML 2016

• 2019-01-31:{1}

  1. COSONet: Compact Second-Order Network for Video Face Recognition
     1. ACCV 2018 oral

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• 2019-02-01:{30}Reid <CVPR(2018)>

  1. Group Consistent Similarity Learning via Deep CRFs for Person Re-Identification
     1. CVPR 2018 oral
  2. Person Transfer GAN to Bridge Domain Gap for Person Re-Identification
     1. CVPR 2018 Spotlight
  3. Disentangled person image generation
     1. CVPR 2018 Spotlight
  4. Unsupervised Person Image Synthesis in Arbitrary Poses
     1. CVPR 2018 Spotlight
  5. Good Appearance Features for Multi-Target Multi-Camera Tracking
     1. CVPR 2018 Spotlight
  6. Diversity Regularized Spatiotemporal Attention for Video-based Person Re-identification
     1. CVPR 2018 Poster
  7. A Pose-Sensitive Embedding for Person Re-Identification with Expanded Cross Neighborhood Re-Ranking
     1. CVPR 2018 Poster
  8. Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification
     1. CVPR 2018 Poster
  9. Human Semantic Parsing for Person Re-identification
     1. CVPR 2018 Poster
  10. Video Person Re-identification with Competitive Snippet-similarity Aggregation and Co-attentive Snippet Embedding
      1. CVPR 2018 Poster
  11. Mask-guided Contrastive Attention Model for Person Re-Identification
      1. CVPR 2018 Poster
  12. Person Re-identification with Cascaded Pairwise Convolutions
      1. CVPR 2018 Poster
  13. Multi-Level Factorisation Net for Person Re-Identification
      1. CVPR 2018 Poster
  14. Attention-Aware Compositional Network for Person Re-identification
      1. CVPR 2018 Poster
  15. Deep Group-shuffling Random Walk for Person Re-identification
      1. CVPR 2018 Poster
  16. Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification
      1. CVPR 2018 Poster
  17. Harmonious Attention Network for Person Re-Identification
      1. CVPR 2018 Poster
  18. Efficient and Deep Person Re-Identification using Multi-Level Similarity
      1. CVPR 2018 Poster
  19. Pose Transferrable Person Re-Identification
      1. CVPR 2018 Poster
  20. Adversarially Occluded Samples for Person Re-identification
      1. CVPR 2018 Poster
  21. Camera Style Adaptation for Person Re-identification
      1. CVPR 2018 Poster
  22. Exploit the Unknown Gradually:~ One-Shot Video-Based Person Re-Identification by Stepwise Learning
      1. CVPR 2018 Poster
  23. Dual Attention Matching Network for Context-Aware Feature Sequence based Person Re-Identification
      1. CVPR 2018 Poster
  24. Easy Identification from Better Constraints: Multi-Shot Person Re-Identification from Reference Constraints
      1. CVPR 2018 Poster
  25. Eliminating Background-bias for Robust Person Re-identification
      1. CVPR 2018 Poster
  26. End-to-End Deep Kronecker-Product Matching for Person Re-identification
      1. CVPR 2018 Poster
  27. Deep Spatial Feature Reconstruction for Partial Person Re-identification
      1. CVPR 2018 Poster
  28. Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatio-temporal Patterns
      1. CVPR 2018 Poster
  29. Multi-shot Pedestrian Re-identification via Sequential Decision Making
      1. CVPR 2018 Poster
  30. Deep Mutual Learning
      1. CVPR 2018 Poster

• 2019-02-02:{18}Reid <ECCV(2018)>

  1. Group Consistent Similarity Learning via Deep CRFs for Person Re-Identification
     1. ECCV 2018
  2. RCAA: Relational Context-Aware Agents for Person Search
     1. ECCV 2018
  3. Generalizing A Person Retrieval Model Hetero- and Homogeneously
     1. ECCV 2018
  4. Domain Adaptation through Synthesis for Unsupervised Person Re-identification
     1. ECCV 2018
  5. Robust Anchor Embedding for Unsupervised Video Person Re-Identification in the Wild},
     1. ECCV 2018
  6. Person Search in Videos with One Portrait Through Visual and Temporal Links
     1. ECCV 2018
  7. Person Search by Multi-Scale Matching
     1. ECCV 2018
  8. Person Re-identification with Deep Similarity-Guided Graph Neural Network
     1. ECCV 2018
  9. Pose-Normalized Image Generation for Person Re-identification
     1. ECCV 2018
  10. Unsupervised Person Re-identification by Deep Learning Tracklet Association
      1. ECCV 2018
  11. Person Search via A Mask-guided Two-stream CNN Model
      1. ECCV 2018
  12. Improving Deep Visual Representation for Person Re-identification by Global and Local Image-language Association},
      1. ECCV 2018
  13. Hard-Aware Point-to-Set Deep Metric for Person Re-identification
      1. ECCV 2018
  14. Reinforced Temporal Attention and Split-Rate Transfer for Depth-Based Person Re-Identification
      1. ECCV 2018
  15. Adversarial Open-World Person Re-Identification
      1. ECCV 2018
  16. Part-Aligned Bilinear Representations for Person Re-Identification
      1. ECCV 2018
  17. Mancs: A Multi-task Attentional Network with Curriculum Sampling for Person Re-identification
      1. ECCV 2018 (market rank1 == 93.1)
  18. Beyond Part Models: Person Retrieval with Refined Part Pooling (and A Strong Convolutional Baseline)
      1. ECCV 2018 (market rank1 == 93.8)

• 2019-02-03:{8}Reid <ICCV(2017)>

  1. A Two Stream Siamese Convolutional Neural Network for Person Re-Identification
     1. ICCV 2017
  2. Learning View-Invariant Features for Person Identification in Temporally Synchronized Videos Taken by Wearable Cameras
     1. ICCV 2017
  3. Deeply-Learned Part-Aligned Representations for Person Re-Identification
     1. ICCV 2017
  4. Unlabeled Samples Generated by GAN Improve the Person Re-Identification Baseline in Vitro
     1. ICCV 2017
  5. Pose-Driven Deep Convolutional Model for Person Re-Identification
     1. ICCV 2017
  6. Jointly Attentive Spatial-Temporal Pooling Networks for Video-Based Person Re-Identification
     1. ICCV 2017
  7. RGB-Infrared Cross-Modality Person Re-Identification
     1. ICCV 2017
  8. Multi-Scale Deep Learning Architectures for Person Re-Identification
     1. ICCV 2017

• 2019-02-04:{8}Reid <CVPR(2017)>

  1. Learning Deep Context-Aware Features Over Body and Latent Parts for Person Re-Identification
     1. CVPR 2017
  2. Beyond Triplet Loss: A Deep Quadruplet Network for Person Re-Identification
     1. CVPR 2017
  3. Person Re-Identification in the Wild
     1. CVPR 2017
  4. One-Shot Metric Learning for Person Re-Identification
     1. CVPR 2017
  5. Joint Detection and Identification Feature Learning for Person Search
     1. CVPR 2017
  6. Point to Set Similarity Based Deep Feature Learning for Person Re-Identification
     1. CVPR 2017
  7. See the Forest for the Trees: Joint Spatial and Temporal Recurrent Neural Networks for Video-Based Person Re-Identification},
     1. CVPR 2017
  8. Consistent-Aware Deep Learning for Person Re-Identification in a Camera Network
     1. CVPR 2017

• 2019-02-05:{15}Reid <NIPS(2018) + IJCAI(2018) + AAAI(2018)>

  1. FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification
     1. NIPS 2018
  2. Cascaded SR-GAN for Scale-Adaptive Low Resolution Person Re-identification
     1. IJCAI 2018
  3. Visible Thermal Person Re-Identification via Dual-Constrained Top-Ranking
     1. IJCAI 2018
  4. Deep View-Aware Metric Learning for Person Re-Identification
     1. IJCAI 2018
  5. SafeNet: Scale-normalization and Anchor-based Feature Extraction Network for Person Re-identification
     1. IJCAI 2018
  6. Cross-Modality Person Re-Identification with Generative Adversarial Training
     1. IJCAI 2018
  7. Adversarial Attribute-Image Person Re-identification
     1. IJCAI 2018
  8. Graph Correspondence Transfer for Person Re-identification
     1. AAAI 2018
  9. Hierarchical Discriminative Learning for Visible Thermal Person Re-Identification
     1. AAAI 2018
  10. Learning Coarse-to-fine Structured Feature Embedding for Vehicle Re-identification
      1. AAAI 2018
  11. Multi-Channel Pyramid Person Matching Network for Person Re-Identification
      1. AAAI 2018
  12. Region-based Quality Estimation Network for Large-scale Person Re-identification
      1. AAAI 2018
  13. semi-supervised Bayesian Attribute Learning for Person Re-identification
      1. AAAI 2018
  14. STemporal-Enhanced Convolutional Network for Person Re-identification
      1. AAAI 2018
  15. Video-based Person Re-identification via Self Paced Weighting
      1. AAAI 2018

• 2019-02-06:{8}Reid <ACM MM(2018)>

  1. A Unified Generative Adversarial Framework for Image Generation and Person Re-Identification
     1. ACM MM 2018
  2. CA3Net: Contextual-Attentional Attribute-Appearance Network for Re-Identification
     1. ACM MM 2018
  3. Learning Discriminative Features with Multiple Granularities for Re-Identification
     1. ACM MM 2018 (Market 95.7)
  4. Local Convolutional Neural Networks for Person Re-Identification
     1. ACM MM 2018
  5. Online Inter-Camera Trajectory Association Exploiting Person Re-Identification and Camera Topology
     1. ACM MM 2018
  6. Person Re-identification with Hierarchical Deep Learning Feature and efficient XQDA Metric
     1. ACM MM 2018
  7. Support Neighbor Loss for Person Re-Identification
     1. ACM MM 2018
  8. Video-based Person Re-identification via Self-Paced Learning and Deep Reinforcement Learning Framework
     1. ACM MM 2018

• 2019-02-07:{17}Bilinear

  1. Bilinear convolutional neural networks for fine-grained visual recognition
     1. TPAMI 2018
  2. Improved bilinear pooling with cnns
     1. Arxiv 2017
  3. Learning Discriminative Features with Multiple Granularities for Re-Identification
     1. ECCV 2018
  4. Towards faster training of global covariance pooling networks by iterative matrix square root normalization
     1. CVPR 2018
  5. Is second-order information helpful for large-scale visual recognition?
     1. ICCV 2017
  6. Grassmann pooling as compact homogeneous bilinear pooling for fine-grained visual classification
     1. ECCV 2018
  7. G2DeNet: Global Gaussian distribution embedding network and its application to visual recognition},
     1. CVPR 2017
  8. Monet: Moments embedding network
     1. CVPR 2018
  9. Attentional pooling for action recognition
     1. NIPS 2017
  10. Kernel pooling for convolutional neural networks
      1. CVPR 2017
  11. Compact generalized non-local network
      1. NIPS 2018
  12. Low-rank bilinear pooling for fine-grained classification
      1. CVPR 2017
  13. Factorized bilinear models for image recognition
      1. ICCV 2017
  14. Higher-order integration of hierarchical convolutional activations for fine-grained visual categorization},
      1. ICCV 2017
  15. Statistically-motivated second-order pooling},
      1. ECCV 2018
  16. Hierarchical bilinear pooling for fine-grained visual recognition
      1. ECCV 2018
  17. Second-order Convolutional Neural Networks
      1. Arxiv 2017

• 2019-02-08:{5} Normalization

  1. Decorrelated batch normalization
     1. CVPR 2018
  2. Projection based weight normalization for deep neural networks
     1. arXiv preprint arXiv:1710.02338
  3. Orthogonal weight normalization: Solution to optimization over multiple dependent stiefel manifolds in deep neural networks
     1. AAAI 2018
  4. Block-normalized gradient method: An empirical study for training deep neural network
     1. Arxiv 2017
  5. Centered Weight Normalization in Accelerating Training of Deep Neural Networks
     1. ICCV 2017
  6. Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
     1. NIPS 2016
  7. Learning a smooth kernel regularizer for convolutional neural networks
     1. Arxiv 2017

• 2019-02-09:{10} AttributeRe-ID

  1. Improving person re-identification by attribute and identity learning
     1. ICCV 2017
  2. Multi-Task Learning with Low Rank Attribute Embedding for Multi-Camera Person Re-Identification
     1. TPAMI 2018
  3. Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification
     1. CVPR 2018
  4. Multi-type attributes driven multi-camera person re-identification
     1. Pattern Recognition 2018
  5. Multi-Level Factorisation Net for Person Re-Identification
     1. CVPR 2018
  6. Attributes-aided Part Detection and Refinement for Person Re-identification
     1. arXiv 2019 02
  7. Attention driven person re-identification
     1. Pattern Recognition 2018
  8. Enhancing Person Retrieval with Joint Person Detection, Attribute Learning, and Identification
     1. PCM 2018
  9. Deep attributes driven multi-camera person re-identification
     1. ECCV 2016
  10. Person re-identification using cnn features learned from combination of attributes
      1. ICPR 2016

• 2019-02-10:{4} AAAI2019-ID

  1. A Bottom-Up Clustering Approach to Unsupervised Person Re-identification
     1. AAAI 2019
  2. Backbone Can Not be Trained at Once: Rolling Back to Pre-trained Network for Person Re-Identification
     1. AAAI 2019
  3. SphereReID: Deep Hypersphere Manifold Embedding for Person Re-Identification
     1. AAAI 2019
  4. Learning Incremental Triplet Margin for Person Re-identification
     1. AAAI 2019

• 2019-02-11:{4} Loss

  1. SphereReID: Deep Hypersphere Manifold Embedding for Person Re-Identification
     1. AAAI 2019
  2. Cosface: Large margin cosine loss for deep face recognition
     1. CVPR 2018
  3. In Defense of the Triplet Loss for Visual Recognition
     1. Arxiv 2019
  4. Support Vector Guided Softmax Loss for Face Recognition
     1. Arxiv 2019

• 2019-04-25:{10} CVPR2019-Reid

  1. Joint Discriminative and Generative Learning for Person Re-identification
     1. CVPR 2019 Oral
  2. Unsupervised Person Re-identification by Soft Multilabel Learning
     1. CVPR 2019 Oral
  3. Learning Context Graph for Person Search
     1. CVPR 2019 Oral
  4. Progressive Pose Attention Transfer for Person Image Generation
     1. CVPR 2019 Oral
  5. Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification
     1. CVPR 2019 Spotlint
  6. Generalizable Person Re-identification by Domain-Invariant Mapping Network
     1. CVPR 2019
  7. Weakly Supervised Person Re-Identification
     1. CVPR 2019
  8. Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification
     1. cvpr 2019
  9. Densely Semantically Aligned Person Re-Identification
     1. CVPR 2019
  10. CapProNet: Deep Feature Learning via Orthogonal Projections onto Capsule Subspaces
      1. NIPS 2018

• 2019-05-28:{8} Graph Convolutional Neural Network

  1. Deep Learning on Graphs: A Survey

     1. Arxiv 2019

  2. Geometric deep learning: going beyond euclidean data},

     1. IEEE Signal Processing Magazine 2017

  3. Relational inductive biases, deep learning, and graph networks

     1. Arxiv 2019

  4. Attention models in graphs: A survey

     1. Arxiv 2019

  5. Graph embedding and extensions: A general framework for dimensionality reduction

     1. TPAMI 2007

  6. Representation learning on graphs: Methods and applications

     1. CVPR 2019

  7. A survey on network embedding

     1. TKDE 2018

  8. Relational inductive biases, deep learning, and graph networks

     1. Arxiv 2018

• 2019-05-29:{4} CVPR2019 Spotlight

  1. Partial Order Pruning: for Best Speed/Accuracy Trade-off in Neural Architecture Search

     1. CVPR 2019

  2. Self-Supervised Convolutional Subspace Clustering Network

     1. CVPR 2019

  3. Perceive Where to Focus: Learning Visibility-aware Part-level Features for Partial Person Re-identification

     1. CVPR 2019

  4. Linkage Based Face Clustering via Graph Convolution Network

     1. CVPR 2019

• 2019-06-12:{5} Cross-modal Graph Embedding

  1. Heterogeneous information network embedding for meta path based proximity

     1. Arxiv 2017

  2. Pathsim: Meta path-based top-k similarity search in heterogeneous information networks

     1. VLDB Endowment 2011

  3. Embedding of embedding (eoe): Joint embedding for coupled heterogeneous networks

     1. WSDM 2017

  4. Heterogeneous metric learning with joint graph regularization for cross-media retrieval

     1. AAAI 2013

  5. Hetero-manifold regularisation for cross-modal hashing

     1. TPAMI 2016

• 2019-06-13:{11} Cross-modal Graph Embedding Related

  1. Structure-Aware Convolutional Neural Networks

     1. NIPS 2018

  2. Unsupervised Image-to-Image Translation Networks

     1. NIPS 2017

  3. Multimodal Unsupervised Image-to-Image Translation

     1. ECCV 2018

  4. Multi-Label Image Recognition with Graph Convolutional Networks

     1. arXiv 2019

  5. Learning to Reduce Dual-level Discrepancy for Infrared-Visible Person Re-identification

     1. CVPR 2019

  6. A^2-Nets: Double Attention Networks

     1. NIPS 2018

  7. Understanding Batch Normalization

     1. NIPS 2018

  8. FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification

     1. NIPS 2018

  9. Graph convolutional neural networks for web-scale recommender systems

     1. KDD 2018 (oral)

  10. Beyond Intra-modality Discrepancy: A Comprehensive Survey of Heterogeneous Person Re-identification},

      1. Arxiv 2019

  11. Joint discriminative and generative learning for person re-identification

      1. CVPR 2019

• 2019-09-04:{11} Cross-modal Graph Embedding Related
  I have already read 227 references so far (2019-06-12-14-26-51).

I have already read 238 references so far (2019-10-16-21-25-08).