activity
20172022
most citedOn Tiny Episodic Memories in Continual Learning

327 citations · 332 across the 5 of their papers we have counts for

collaborators

17 papers

cs.CV20224 cited

Retrieval Augmented Classification for Long-Tail Visual Recognition

Alexander Long, Wei Yin, Thalaiyasingam Ajanthan +6

We introduce Retrieval Augmented Classification (RAC), a generic approach to augmenting standard image classification pipelines with an explicit retrieval module. RAC consists of a…

cs.CV2021

Few-shot Weakly-Supervised Object Detection via Directional Statistics

Amirreza Shaban, Amir Rahimi, Thalaiyasingam Ajanthan +2

Detecting novel objects from few examples has become an emerging topic in computer vision recently. However, these methods need fully annotated training images to learn new object…

cs.CV2021

RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs

Zhiwei Xu, Thalaiyasingam Ajanthan, Vibhav Vineet +1

Although 3D Convolutional Neural Networks are essential for most learning based applications involving dense 3D data, their applicability is limited due to excessive memory and com…

cs.CV20201 cited

Refining Semantic Segmentation with Superpixel by Transparent Initialization and Sparse Encoder

Zhiwei Xu, Thalaiyasingam Ajanthan, Richard Hartley

Although deep learning greatly improves the performance of semantic segmentation, its success mainly lies in object central areas without accurate edges. As superpixels are a popul…

cs.CV2020

RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs

Zhiwei Xu, Thalaiyasingam Ajanthan, Vibhav Vineet +1

Although 3D Convolutional Neural Networks (CNNs) are essential for most learning based applications involving dense 3D data, their applicability is limited due to excessive memory…

cs.CV2020

Pairwise Similarity Knowledge Transfer for Weakly Supervised Object Localization

Amir Rahimi, Amirreza Shaban, Thalaiyasingam Ajanthan +2

Weakly Supervised Object Localization (WSOL) methods only require image level labels as opposed to expensive bounding box annotations required by fully supervised algorithms. We st…