Representation Learning

End-To-End Learning of Deformable Mixture of Parts and Deep Convolutional Neural Networks for Human Pose Estimation CVPR 2016 Exponential Family Embeddings NeurIPS 2016 Fashion Style in 128 Floats: Joint Ranking and Classification Using Weak Data for Feature Extraction CVPR 2016 Fast Parameter Inference in Nonlinear Dynamical Systems using Iterative Gradient Matching ICML 2016 GAKE: Graph Aware Knowledge Embedding COLING 2016 Gaussian Conditional Random Field Network for Semantic Segmentation CVPR 2016 Hierarchical Recurrent Neural Encoder for Video Representation With Application to Captioning CVPR 2016 Highlight Detection With Pairwise Deep Ranking for First-Person Video Summarization CVPR 2016 Hybrid Orthogonal Projection and Estimation (HOPE): A New Framework to Learn Neural Networks JMLR 2016 Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections NeurIPS 2016 In Defense of Sparse Tracking: Circulant Sparse Tracker CVPR 2016 Inverting Visual Representations With Convolutional Networks CVPR 2016 Iterative Instance Segmentation CVPR 2016 Knowledge-Driven Event Embedding for Stock Prediction COLING 2016 Learning Convolutional Neural Networks for Graphs ICML 2016 Learning Deep Embeddings with Histogram Loss NeurIPS 2016 Learning Deep Features for Discriminative Localization CVPR 2016 Learning Deep Parsimonious Representations NeurIPS 2016 Learning Deep Representation for Imbalanced Classification CVPR 2016 Learning Deep Structure-Preserving Image-Text Embeddings CVPR 2016 Learning Granger Causality for Hawkes Processes ICML 2016 Learning Local Image Descriptors With Deep Siamese and Triplet Convolutional Networks by Minimising Global Loss Functions CVPR 2016 Learning Relaxed Deep Supervision for Better Edge Detection CVPR 2016 Learning Structured Inference Neural Networks With Label Relations CVPR 2016 Learning to Match Aerial Images With Deep Attentive Architectures CVPR 2016