Computer Vision

How Many Bits Does it Take for a Stimulus to Be Salient? CVPR 2015 Hypercolumns for Object Segmentation and Fine-Grained Localization CVPR 2015 Image Specificity CVPR 2015 Improving Image Classification With Location Context ICCV 2015 Intrinsic Decomposition of Image Sequences From Local Temporal Variations ICCV 2015 Joint Vanishing Point Extraction and Tracking CVPR 2015 Label Consistent Quadratic Surrogate Model for Visual Saliency Prediction CVPR 2015 Learning Deep Representations for Ground-to-Aerial Geolocalization CVPR 2015 Learning From Massive Noisy Labeled Data for Image Classification CVPR 2015 Learning Ordinal Relationships for Mid-Level Vision ICCV 2015 Learning to Compare Image Patches via Convolutional Neural Networks CVPR 2015 Learning To Look Up: Realtime Monocular Gaze Correction Using Machine Learning CVPR 2015 Learning Wake-Sleep Recurrent Attention Models NeurIPS 2015 Long-Term Recurrent Convolutional Networks for Visual Recognition and Description CVPR 2015 MAP Disparity Estimation Using Hidden Markov Trees ICCV 2015 Mid-Level Deep Pattern Mining CVPR 2015 More About VLAD: A Leap From Euclidean to Riemannian Manifolds CVPR 2015 MRF Optimization by Graph Approximation CVPR 2015 Multi-Task Deep Visual-Semantic Embedding for Video Thumbnail Selection CVPR 2015 Multi-View Convolutional Neural Networks for 3D Shape Recognition ICCV 2015 One Shot Learning via Compositions of Meaningful Patches ICCV 2015 On Linear Structure From Motion for Light Field Cameras ICCV 2015 On the Appearance of Translucent Edges CVPR 2015 On the Minimal Problems of Low-Rank Matrix Factorization CVPR 2015 On the Relationship Between Visual Attributes and Convolutional Networks CVPR 2015