gvnn: Neural Network Library for Geometric Computer Vision
We introduce gvnn, a neural network library in Torch aimed towards bridging the gap between classic geometric computer vision and deep learning. Inspired by the recent success of Spatial Transformer Networks, we propose several new layers which are often used as parametric transformations on the data in geometric computer vision. These layers can be inserted within a neural network much in the spirit of the original spatial transformers and allow backpropagation to enable end-to-end learning of a network involving any domain knowledge in geometric computer vision. This opens up applications in learning invariance to 3D geometric transformation for place recognition, end-to-end visual odometry, depth estimation and unsupervised learning through warping with a parametric transformation for image reconstruction error.
Code (1)
Tasks
Image ReconstructionVisual OdometryMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Graph Variate Neural Networks
Modelling dynamically evolving spatio-temporal signals is a prominent challenge in the Graph Neural Network (GNN) literature. Notably, GNNs assume an existing underlying graph structure. While this underlying structure m…
Graph Neural NetworkAnalogVNN: A fully modular framework for modeling and optimizing photonic neural networks
AnalogVNN, a simulation framework built on PyTorch which can simulate the effects of optoelectronic noise, limited precision, and signal normalization present in photonic neural network accelerators. We use this framewor…
BIG-bench Machine LearningGPUHyperparameter OptimizationManagementChainerCV: a Library for Deep Learning in Computer Vision
Despite significant progress of deep learning in the field of computer vision, there has not been a software library that covers these methods in a unifying manner. We introduce ChainerCV, a software library that is inte…
Deep Learningobject-detectionObject DetectionSemantic SegmentationDroneVis: Versatile Computer Vision Library for Drones
This paper introduces DroneVis, a novel library designed to automate computer vision algorithms on Parrot drones. DroneVis offers a versatile set of features and provides a diverse range of computer vision tasks along wi…
Volkit: A Performance-Portable Computer Vision Library for 3D Volumetric Data
We present volkit, an open source library with high performance implementations of image manipulation and computer vision algorithms that focus on 3D volumetric representations. Volkit implements a cross-platform, perfor…
Image Manipulation