CBAM: Convolutional Block Attention Module
We propose Convolutional Block Attention Module (CBAM), a simple yet effective attention module for feed-forward convolutional neural networks. Given an intermediate feature map...
Publications
View AllThe Unreasonable Effectiveness of Deep Features as a Perceptual Metric
While it is nearly effortless for humans to quickly assess the perceptual similarity between two images, the underlying processes are thought to be quite complex. Despite this, ...
A scalable active framework for region annotation in 3D shape collections
Large repositories of 3D shapes provide valuable input for data-driven analysis and modeling tools. They are especially powerful once annotated with semantic information such as...
Fast Image Super-Resolution Based on In-Place Example Regression
We propose a fast regression model for practical single image super-resolution based on in-place examples, by leveraging two fundamental super-resolution approaches- learning fr...
Reversible Recursive Instance-Level Object Segmentation
In this work, we propose a novel Reversible Recursive Instance-level Object Segmentation (R2-IOS) framework to address the challenging instance-level object segmentation task. R...
Affiliated Researchers
Institution Info
- Type
- company
- Country
- US
- Publications
- 5
- Citations
- 32,454
External Links
Identifiers
- ROR
- https://ror.org/059tvcg64