Keywords
Affiliated Institutions
Related Publications
Scene labeling with LSTM recurrent neural networks
This paper addresses the problem of pixel-level segmentation and classification of scene images with an entirely learning-based approach using Long Short Term Memory (LSTM) recu...
Residual Conv-Deconv Grid Network for Semantic Segmentation
This paper presents GridNet, a new Convolutional Neural Network (CNN)\narchitecture for semantic image segmentation (full scene labelling). Classical\nneural networks are implem...
CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
We propose a network for Congested Scene Recognition called CSRNet to provide a data-driven and deep learning method that can understand highly congested scenes and perform accu...
Scene Segmentation with DAG-Recurrent Neural Networks
In this paper, we address the challenging task of scene segmentation. In order to capture the rich contextual dependencies over image regions, we propose Directed Acyclic Graph-...
A space-sweep approach to true multi-image matching
The problem of determining feature correspondences across multiple views is considered. The term "true multi-image" matching is introduced to describe techniques that make full ...
Publication Info
- Year
- 2019
- Type
- article
- Volume
- 98
- Pages
- 107038-107038
- Citations
- 1021
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1016/j.patcog.2019.107038