Search Results for author: Joshua Knights

Found 3 papers, 1 papers with code

InCloud: Incremental Learning for Point Cloud Place Recognition

no code implementations2 Mar 2022 Joshua Knights, Peyman Moghadam, Milad Ramezani, Sridha Sridharan, Clinton Fookes

In this paper we address the problem of incremental learning for point cloud place recognition and introduce InCloud, a structure-aware distillation-based approach which preserves the higher-order structure of the network's embedding space.

Incremental Learning

Point Cloud Segmentation Using Sparse Temporal Local Attention

no code implementations1 Dec 2021 Joshua Knights, Peyman Moghadam, Clinton Fookes, Sridha Sridharan

Point clouds are a key modality used for perception in autonomous vehicles, providing the means for a robust geometric understanding of the surrounding environment.

Autonomous Vehicles Frame +1

Temporally Coherent Embeddings for Self-Supervised Video Representation Learning

1 code implementation21 Mar 2020 Joshua Knights, Ben Harwood, Daniel Ward, Anthony Vanderkop, Olivia Mackenzie-Ross, Peyman Moghadam

The proposed method exploits inherent structure of unlabeled video data to explicitly enforce temporal coherency in the embedding space, rather than indirectly learning it through ranking or predictive proxy tasks.

Metric Learning Representation Learning +2

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