Papers

2,653 papers found
Learning Visual Attributes
Vittorio Ferrari, Andrew Zisserman
2007 NIPS
Bilinear classifiers for visual recognition
Hamed Pirsiavash, Deva Ramanan, Charless C. Fowlkes
2009 NIPS
No evidence for active sparsification in the visual cortex
Pietro Berkes, Ben White, Jozsef Fiser
2009 NIPS
2010 NIPS
Kernel Descriptors for Visual Recognition
Liefeng Bo, Xiaofeng Ren, Dieter Fox
2010 NIPS
Learning Convolutional Feature Hierarchies for Visual Recognition
Koray Kavukcuoglu, Pierre Sermanet, Y-lan Boureau et al.
2010 NIPS
Structural epitome: a way to summarize one’s visual experience
Nebojsa Jojic, Alessandro Perina, Vittorio Murino
2010 NIPS
Multi-View Learning of Word Embeddings via CCA
Paramveer Dhillon, Dean P. Foster, Lyle H. Ungar
2011 NIPS
Predicting response time and error rates in visual search
Bo Chen, Vidhya Navalpakkam, Pietro Perona
2011 NIPS
Learning a Tree of Metrics with Disjoint Visual Features
Kristen Grauman, Fei Sha, Sung Ju Hwang
2011 NIPS
Learning visual motion in recurrent neural networks
Marius Pachitariu, Maneesh Sahani
2012 NIPS
Controlled Recognition Bounds for Visual Learning and Exploration
Vasiliy Karasev, Alessandro Chiuso, Stefano Soatto
2012 NIPS
A lattice filter model of the visual pathway
Karol Gregor, Dmitri B. Chklovskii
2012 NIPS
Fusion with Diffusion for Robust Visual Tracking
Yu Zhou, Xiang Bai, Wenyu Liu et al.
2012 NIPS
Kernel Latent SVM for Visual Recognition
Weilong Yang, Yang Wang, Arash Vahdat et al.
2012 NIPS
Reshaping Visual Datasets for Domain Adaptation
Boqing Gong, Kristen Grauman, Fei Sha
2013 NIPS
DeViSE: A Deep Visual-Semantic Embedding Model
Andrea Frome, Greg S Corrado, Jon Shlens et al.
2013 NIPS
Mid-level Visual Element Discovery as Discriminative Mode Seeking
Carl Doersch, Abhinav Gupta, Alexei A Efros
2013 NIPS
An Autoencoder Approach to Learning Bilingual Word Representations
Sarath Chandar A P, Stanislas Lauly, Hugo Larochelle et al.
2014 NIPS
Recurrent Models of Visual Attention
Volodymyr Mnih, Nicolas Heess, Alex Graves et al.
2014 NIPS