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Neural Networks

11300 directly classified papers

Papers per year

Papers

OctNet: Learning Deep 3D Representations at High Resolutions CVPR 2017
Fractal Dimension Invariant Filtering and Its CNN-Based Implementation CVPR 2017
Learning Deep Match Kernels for Image-Set Classification CVPR 2017
Deeply Supervised Salient Object Detection With Short Connections CVPR 2017
Residual Attention Network for Image Classification CVPR 2017
Locality-Sensitive Deconvolution Networks With Gated Fusion for RGB-D Indoor Semantic Segmentation CVPR 2017
Deep Image Matting CVPR 2017
Kernel Pooling for Convolutional Neural Networks CVPR 2017
LCNN: Lookup-Based Convolutional Neural Network CVPR 2017
Optical Flow Requires Multiple Strategies (but Only One Network) CVPR 2017
Spatio-Temporal Self-Organizing Map Deep Network for Dynamic Object Detection From Videos CVPR 2017
Hard Mixtures of Experts for Large Scale Weakly Supervised Vision CVPR 2017
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning NIPS 2017
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions NIPS 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? NIPS 2017
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation CVPR 2017
FlowNet 2.0: Evolution of Optical Flow Estimation With Deep Networks CVPR 2017
PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs NIPS 2017
On-the-fly Operation Batching in Dynamic Computation Graphs NIPS 2017
A graph-theoretic approach to multitasking NIPS 2017
Fast-Slow Recurrent Neural Networks NIPS 2017
A simple neural network module for relational reasoning NIPS 2017
Preventing Gradient Explosions in Gated Recurrent Units NIPS 2017
Learning Hierarchical Information Flow with Recurrent Neural Modules NIPS 2017
The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process NIPS 2017