Then, an additional penalty term, which is in proportion to the ratio of instance FPR overall FPR, is introduced into the denominator of the softmax-based loss.
Deep learning has become the dominant approach in coping with various tasks in Natural LanguageProcessing (NLP).
This paper presents a simple yet effective approach to modeling space-time correspondences in the context of video object segmentation.
Ranked #1 on Semi-Supervised Video Object Segmentation on DAVIS 2017 (val) (using extra training data)
Inspired by the common painting process of drawing a draft and revising the details, we introduce a novel feed-forward method named Laplacian Pyramid Network (LapStyle).
Furthermore, the results are with distinctive artistic style and retain the anisotropic semantic information.
The critical element of RCNN is the recurrent convolutional layer (RCL), which incorporates recurrent connections between neurons in the standard convolutional layer.
In this paper, we question if self-supervised learning provides new properties to Vision Transformer (ViT) that stand out compared to convolutional networks (convnets).
Ranked #1 on Video Object Detection on DAVIS 2017
We show that viewing graphs as sets of node features and incorporating structural and positional information into a transformer architecture is able to outperform representations learned with classical graph neural networks (GNNs).