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Neural Networks

11300 directly classified papers

Papers per year

Papers

Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation NIPS 2016
R-FCN: Object Detection via Region-based Fully Convolutional Networks NIPS 2016
CliqueCNN: Deep Unsupervised Exemplar Learning NIPS 2016
Universal Correspondence Network NIPS 2016
Doubly Convolutional Neural Networks NIPS 2016
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks NIPS 2016
Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles NIPS 2016
Swapout: Learning an ensemble of deep architectures NIPS 2016
Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes NIPS 2016
LightRNN: Memory and Computation-Efficient Recurrent Neural Networks NIPS 2016
Composition-Preserving Deep Photo Aesthetics Assessment CVPR 2016
Do Computational Models Differ Systematically From Human Object Perception? CVPR 2016
Accurate Image Super-Resolution Using Very Deep Convolutional Networks CVPR 2016
Learning to Assign Orientations to Feature Points CVPR 2016
Temporal Action Localization in Untrimmed Videos via Multi-Stage CNNs CVPR 2016
Part-Stacked CNN for Fine-Grained Visual Categorization CVPR 2016
Efficient Training of Very Deep Neural Networks for Supervised Hashing CVPR 2016
3D Shape Attributes CVPR 2016
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network CVPR 2016
Detecting Events and Key Actors in Multi-Person Videos CVPR 2016
Temporal Action Localization With Pyramid of Score Distribution Features CVPR 2016
ProNet: Learning to Propose Object-Specific Boxes for Cascaded Neural Networks CVPR 2016
DAG-Recurrent Neural Networks For Scene Labeling CVPR 2016
Learning Multi-Domain Convolutional Neural Networks for Visual Tracking CVPR 2016
RAID-G: Robust Estimation of Approximate Infinite Dimensional Gaussian With Application to Material Recognition CVPR 2016