17 citations · 37 across the 6 of their papers we have counts for
10 papers · 1 filter
Physical Adversarial Attacks on an Aerial Imagery Object Detector
Andrew Du, Bo Chen, Tat-Jun Chin +4
Deep neural networks (DNNs) have become essential for processing the vast amounts of aerial imagery collected using earth-observing satellite platforms. However, DNNs are vulnerabl…
Generalised Zero-Shot Learning with Domain Classification in a Joint Semantic and Visual Space
Rafael Felix, Ben Harwood, Michele Sasdelli +1
Generalised zero-shot learning (GZSL) is a classification problem where the learning stage relies on a set of seen visual classes and the inference stage aims to identify both the…
Generalised Zero-Shot Learning with a Classifier Ensemble over Multi-Modal Embedding Spaces
Rafael Felix, Ben Harwood, Michele Sasdelli +1
Generalised zero-shot learning (GZSL) methods aim to classify previously seen and unseen visual classes by leveraging the semantic information of those classes. In the context of G…
Real-time tracker with fast recovery from target loss
Alessandro Bay, Panagiotis Sidiropoulos, Eduard Vazquez +1
In this paper, we introduce a variation of a state-of-the-art real-time tracker (CFNet), which adds to the original algorithm robustness to target loss without a significant comput…
Multi-modal Ensemble Classification for Generalized Zero Shot Learning
Rafael Felix, Michele Sasdelli, Ian Reid +1
Generalized zero shot learning (GZSL) is defined by a training process containing a set of visual samples from seen classes and a set of semantic samples from seen and unseen class…
Instance Retrieval at Fine-grained Level Using Multi-Attribute Recognition
Roshanak Zakizadeh, Yu Qian, Michele Sasdelli +1
In this paper, we present a method for instance ranking and retrieval at fine-grained level based on the global features extracted from a multi-attribute recognition model which is…