3 accepted papers
Recent advances in Vision Transformers (ViTs) have significantly improved the performance of Visual Place Recognition (VPR), but their high computational cost—due to the quadratic complexity of self-attention—limits their practical deployment in real-world scenarios. To address this challenge, we pr…
Deep Neural Networks (DNNs) are one of the most powerful tools for prediction, but many of them implicitly assume that the data are statistically independent. However, in the real world, it is common for large-scale data to be clustered with temporal-spatial correlation structures. Variational appro…
Unsupervised video object segmentation (UVOS) is a per-pixel binary labeling problem which aims at separating the foreground object from the background in the video without using the ground truth (GT) mask of the foreground object. Most of the previous UVOS models use the first frame or the entire v…