Search Results for author: Yan Zuo

Found 9 papers, 3 papers with code

Divide and Conquer: Rethinking the Training Paradigm of Neural Radiance Fields

no code implementations29 Jan 2024 Rongkai Ma, Leo Lebrat, Rodrigo Santa Cruz, Gil Avraham, Yan Zuo, Clinton Fookes, Olivier Salvado

Neural radiance fields (NeRFs) have exhibited potential in synthesizing high-fidelity views of 3D scenes but the standard training paradigm of NeRF presupposes an equal importance for each image in the training set.

Bayesian Optimisation for Mixed-Variable Inputs using Value Proposals

no code implementations10 Feb 2022 Yan Zuo, Amir Dezfouli, Iadine Chades, David Alexander, Benjamin Ward Muir

Many real-world optimisation problems are defined over both categorical and continuous variables, yet efficient optimisation methods such asBayesian Optimisation (BO) are not designed tohandle such mixed-variable search spaces.

Bayesian Optimisation

Learning Instance and Task-Aware Dynamic Kernels for Few Shot Learning

1 code implementation7 Dec 2021 Rongkai Ma, Pengfei Fang, Gil Avraham, Yan Zuo, Tianyu Zhu, Tom Drummond, Mehrtash Harandi

A principle way of achieving few-shot learning is to realize a model that can rapidly adapt to the context of a given task.

Few-Shot Learning Novel Concepts

Localising In Complex Scenes Using Balanced Adversarial Adaptation

no code implementations9 Nov 2020 Gil Avraham, Yan Zuo, Tom Drummond

Domain adaptation and generative modelling have collectively mitigated the expensive nature of data collection and labelling by leveraging the rich abundance of accurate, labelled data in simulation environments.

Domain Adaptation

Residual Likelihood Forests

no code implementations4 Nov 2020 Yan Zuo, Tom Drummond

This paper presents a novel ensemble learning approach called Residual Likelihood Forests (RLF).

Ensemble Learning

EMPNet: Neural Localisation and Mapping Using Embedded Memory Points

1 code implementation ICCV 2019 Gil Avraham, Yan Zuo, Thanuja Dharmasiri, Tom Drummond

Continuously estimating an agent's state space and a representation of its surroundings has proven vital towards full autonomy.

Traversing Latent Space using Decision Ferns

no code implementations6 Dec 2018 Yan Zuo, Gil Avraham, Tom Drummond

The practice of transforming raw data to a feature space so that inference can be performed in that space has been popular for many years.

Generative Adversarial Forests for Better Conditioned Adversarial Learning

no code implementations14 May 2018 Yan Zuo, Gil Avraham, Tom Drummond

In recent times, many of the breakthroughs in various vision-related tasks have revolved around improving learning of deep models; these methods have ranged from network architectural improvements such as Residual Networks, to various forms of regularisation such as Batch Normalisation.

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