CellTypeGraph: A New Geometric Computer Vision Benchmark
Classifying all cells in an organ is a relevant and difficult problem from plant developmental biology. We here abstract the problem into a new benchmark for node classification in a geo-referenced graph. Solving it requires learning the spatial layout of the organ including symmetries. To allow the convenient testing of new geometrical learning methods, the benchmark of Arabidopsis thaliana ovules is made available as a PyTorch data loader, along with a large number of precomputed features. Finally, we benchmark eight recent graph neural network architectures, finding that DeeperGCN currently works best on this problem.
Code (2)
Tasks
Graph Neural NetworkNode ClassificationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
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 …
Image ReconstructionVisual OdometryGeoclidean: Few-Shot Generalization in Euclidean Geometry
Euclidean geometry is among the earliest forms of mathematical thinking. While the geometric primitives underlying its constructions, such as perfect lines and circles, do not often occur in the natural world, humans rar…
BenchmarkingComputer Vision Modeling of the Development of Geometric and Numerical Concepts in Humans
Mathematical thinking is a fundamental aspect of human cognition. Cognitive scientists have investigated the mechanisms that underlie our ability to thinking geometrically and numerically, to take two prominent examples,…
Image ClassificationVFM-VLM: Vision Foundation Model and Vision Language Model based Visual Comparison for 3D Pose Estimation
Vision Foundation Models (VFMs) and Vision Language Models (VLMs) have revolutionized computer vision by providing rich semantic and geometric representations. This paper presents a comprehensive visual comparison betwee…
3D Pose EstimationSome Aspects of Geometric Computer Vision for Analysing Dynamical Scenes focusing Automotive Applications
This draft summarizes some basics about geometric computer vision needed to implement efficient computer vision algorithms for applications that use measurements from at least one digital camera mounted on a moving platf…
Optical Flow EstimationVisual Odometry