image classification

Analyzing Classifiers: Fisher Vectors and Deep Neural Networks CVPR 2016 An Empirical Evaluation of Current Convolutional Architectures' Ability to Manage Nuisance Location and Scale Variability CVPR 2016 Approximate Log-Hilbert-Schmidt Distances Between Covariance Operators for Image Classification CVPR 2016 Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification ICML 2016 Backtracking ScSPM Image Classifier for Weakly Supervised Top-Down Saliency CVPR 2016 Blockout: Dynamic Model Selection for Hierarchical Deep Networks CVPR 2016 Compact Bilinear Pooling CVPR 2016 Convolutional Neural Fabrics NeurIPS 2016 DAG-Recurrent Neural Networks For Scene Labeling CVPR 2016 Deep Decision Network for Multi-Class Image Classification CVPR 2016 DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks CVPR 2016 Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data Is Continuous and Weakly Labelled CVPR 2016 DisturbLabel: Regularizing CNN on the Loss Layer CVPR 2016 Doubly Convolutional Neural Networks NeurIPS 2016 Dynamic Capacity Networks ICML 2016 End-to-End Kernel Learning with Supervised Convolutional Kernel Networks NeurIPS 2016 Fashion Style in 128 Floats: Joint Ranking and Classification Using Weak Data for Feature Extraction CVPR 2016 Fine-Grained Image Classification by Exploring Bipartite-Graph Labels CVPR 2016 Group Equivariant Convolutional Networks ICML 2016 Hierarchical Gaussian Descriptor for Person Re-Identification CVPR 2016 iLab-20M: A Large-Scale Controlled Object Dataset to Investigate Deep Learning CVPR 2016 Integrated perception with recurrent multi-task neural networks NeurIPS 2016 InterActive: Inter-Layer Activeness Propagation CVPR 2016 Learned Region Sparsity and Diversity Also Predicts Visual Attention NeurIPS 2016 Learning Structured Inference Neural Networks With Label Relations CVPR 2016