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Found 4 papers, 1 papers with code
MemoNav: Working Memory Model for Visual Navigation
Subsequently, a graph attention module encodes the retained STM and the LTM to generate working memory (WM) which contains the scene features essential for efficient navigation.
Informative Data Mining for One-Shot Cross-Domain Semantic Segmentation
One-shot domain adaptation methods attempt to overcome these challenges by transferring the pre-trained source model to the target domain using only one target data.
SSF: Accelerating Training of Spiking Neural Networks with Stabilized Spiking Flow
Surrogate gradient (SG) is one of the most effective approaches for training spiking neural networks (SNNs).
MemoNav: Selecting Informative Memories for Visual Navigation
To address this limitation, we present the MemoNav, a novel memory mechanism for image-goal navigation, which retains the agent's informative short-term memory and long-term memory to improve the navigation performance on a multi-goal task.
