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Xiangyu Zhang
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Robust Recovery of Subspace Structures by Low-Rank Representation
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Attention Is All You Need
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DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
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Densely Connected Convolutional Networks
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Pyramid Scene Parsing Network
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Fully convolutional networks for semantic segmentation
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Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
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2016
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Kaiming He
Ross Girshick
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Convolutional Neural Networks with Alternately Updated Clique
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2018
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Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining
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2018
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
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Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
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Kaiming He
Xiangyu Zhang
Shaoqing Ren
Jian Sun
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Hadamard Product for Low-rank Bilinear Pooling
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Kyoung-Woon On
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Non-local Neural Networks
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2018
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Ross Girshick
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Joint Unsupervised Learning of Deep Representations and Image Clusters
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RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation
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Anton Milan
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Learning Phrase Representations using RNN EncoderâDecoder for Statistical Machine Translation
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Feature Pyramid Networks for Object Detection
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2017
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Piotr DollĂĄr
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Essential Tensor Learning for Multi-View Spectral Clustering
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2019
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Zhouchen Lin
Hongbin Zha
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Very Deep Convolutional Networks for Large-Scale Image Recognition
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Unsupervised Deep Embedding for Clustering Analysis
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Aggregated Residual Transformations for Deep Neural Networks
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Ross Girshick
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Neural Motifs: Scene Graph Parsing with Global Context
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Deep Comprehensive Correlation Mining for Image Clustering
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2019
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Jianlong Wu
Keyu Long
Fei Wang
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Zhouchen Lin
Hongbin Zha
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Attention is All you Need
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2017
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Ashish Vaswani
Noam Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan N. Gomez
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Illia Polosukhin
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Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering
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Dual Attention Network for Scene Segmentation
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Jing Liu
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Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization
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Rethinking Atrous Convolution for Semantic Image Segmentation
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Deep roto-translation scattering for object classification
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Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation
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Scene Graph Generation by Iterative Message Passing
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Going deeper with convolutions
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On Unifying Multi-view Self-Representations for Clustering by Tensor Multi-rank Minimization
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Large Kernel Matters â Improve Semantic Segmentation by Global Convolutional Network
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Understanding image representations by measuring their equivariance and equivalence
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Low-rank Matrix Recovery via Iteratively Reweighted Least Squares Minimization
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COCO-Stuff: Thing and Stuff Classes in Context
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Pixelwise Instance Segmentation with a Dynamically Instantiated Network
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Novel Methods for Multilinear Data Completion and De-noising Based on Tensor-SVD
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Fully Convolutional Instance-Aware Semantic Segmentation
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Wider or Deeper: Revisiting the ResNet Model for Visual Recognition
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