convolution operator
PointCNN: Convolution On X-Transformed Points
We present a simple and general framework for feature learning from point cloud. The key to the success of CNNs is the convolution operator that is capable of leveraging spatially-local correlation in data represented densely in grids (e.g.
Group Equivariant Capsule Networks
Jan Eric Lenssen, Matthias Fey, Pascal Libuschewski
Wepresentgroupequivariant capsule networks,aframeworktointroduce guaranteed equivariance and invariance properties to the capsule network idea.
- North America > Canada > Quebec > Montreal (0.04)
- North America > Canada > Ontario > Toronto (0.04)
- Europe > Germany (0.04)
NeurVPS: Neural Vanishing Point Scanning via Conic Convolution
Yichao Zhou, Haozhi Qi, Jingwei Huang, Yi Ma
Neural Information Processing Systems http://nips.cc/
- North America > United States > California > Santa Clara County > Palo Alto (0.04)
- North America > Canada (0.04)
SemanticDiffusionNetworkforSemantic Segmentation
A key challenge in semantic segmentation is how to improve the boundary quality of segmentation results (Figure 1).
- Asia > South Korea > Incheon > Incheon (0.04)
- North America > Puerto Rico > San Juan > San Juan (0.04)
Protein Interface Prediction using Graph Convolutional Networks
Alex Fout, Jonathon Byrd, Basir Shariat, Asa Ben-Hur
Neural Information Processing Systems http://nips.cc/
- North America > United States > Colorado > Larimer County > Fort Collins (0.05)
- North America > United States > California > Los Angeles County > Long Beach (0.04)
PointCNN: Convolution On X-Transformed Points
We present a simple and general framework for feature learning from point cloud. The key to the success of CNNs is the convolution operator that is capable of leveraging spatially-local correlation in data represented densely in grids (e.g.
NeurVPS: Neural Vanishing Point Scanning via Conic Convolution
Yichao Zhou, Haozhi Qi, Jingwei Huang, Yi Ma
Neural Information Processing Systems http://nips.cc/
- North America > United States > California > Santa Clara County > Palo Alto (0.04)
- North America > Canada > British Columbia > Metro Vancouver Regional District > Vancouver (0.04)
- Media > Photography (0.46)
- Information Technology (0.46)
- North America > United States > California (0.15)
- North America > Canada (0.04)
Revisiting Sliced Wasserstein on Images: From Vectorization to Convolution
However, this approach has two limitations.
- North America > United States > Texas > Travis County > Austin (0.14)
- Asia > Middle East > Jordan (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
- Asia > Japan > Honshū > Tōhoku > Fukushima Prefecture > Fukushima (0.04)