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Found 5 papers, 0 papers with code
NID-SLAM: Neural Implicit Representation-based RGB-D SLAM in dynamic environments
In this paper we present NID-SLAM, which significantly improves the performance of neural SLAM in dynamic environments.
Equirectangular image construction method for standard CNNs for Semantic Segmentation
In addition, there are few publicly dataset of equirectangular images with labels, which presents a challenge for standard CNNs models to process equirectangular images effectively.
Transformers satisfy
The Propositional Satisfiability Problem (SAT), and more generally, the Constraint Satisfaction Problem (CSP), are mathematical questions defined as finding an assignment to a set of objects that satisfies a series of constraints.
TWIN GRAPH CONVOLUTIONAL NETWORKS: GCN WITH DUAL GRAPH SUPPORT FOR SEMI-SUPERVISED LEARNING
Graph Neural Networks as a combination of Graph Signal Processing and Deep Convolutional Networks shows great power in pattern recognition in non-Euclidean domains.
HUGE2: a Highly Untangled Generative-model Engine for Edge-computing
In this work, we propose a Highly Untangled Generative-model Engine for Edge-computing or HUGE2 for accelerating these two special convolutions on the edge-computing platform by decomposing the kernels and untangling these smaller convolutions by performing basic matrix multiplications.
