research
∙
06/03/2022
Zero-Shot Bird Species Recognition by Learning from Field Guides
We exploit field guides to learn bird species recognition, in particular...
share
research
∙
03/27/2022
Learning Graph Regularisation for Guided Super-Resolution
We introduce a novel formulation for guided super-resolution. Its core i...
research
∙
02/10/2022
A Deep Learning Approach for Digital ColorReconstruction of Lenticular Films
We propose the first accurate digitization and color reconstruction proc...
research
∙
06/07/2021
Digital Taxonomist: Identifying Plant Species in Citizen Scientists' Photographs
Automatic identification of plant specimens from amateur photographs cou...
research
∙
05/24/2021
Mapping oil palm density at country scale: An active learning approach
Accurate mapping of oil palm is important for understanding its past and...
research
∙
03/04/2021
PC2WF: 3D Wireframe Reconstruction from Raw Point Clouds
We introduce PC2WF, the first end-to-end trainable deep network architec...
research
∙
08/25/2020
Deep Active Learning in Remote Sensing for data efficient Change Detection
We investigate active learning in the context of deep neural network mod...
research
∙
03/20/2020
Privileged Pooling: Supervised attention-based pooling for compensating dataset bias
In this paper we propose a novel supervised image classification method ...
research
∙
11/25/2019
Gating Revisited: Deep Multi-layer RNNs That Can Be Trained
We propose a new stackable recurrent cell (STAR) for recurrent neural ne...
research
∙
04/02/2019
Guided Super-Resolution as a Learned Pixel-to-Pixel Transformation
Guided super-resolution is a unifying framework for several computer vis...
research
∙
11/20/2017