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Found 9 papers, 3 papers with code
ViewFusion: Towards Multi-View Consistency via Interpolated Denoising
Novel-view synthesis through diffusion models has demonstrated remarkable potential for generating diverse and high-quality images.
Divide and Conquer: Rethinking the Training Paradigm of Neural Radiance Fields
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
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.
Learning Instance and Task-Aware Dynamic Kernels for Few Shot Learning
A principle way of achieving few-shot learning is to realize a model that can rapidly adapt to the context of a given task.
Localising In Complex Scenes Using Balanced Adversarial Adaptation
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.
Residual Likelihood Forests
This paper presents a novel ensemble learning approach called Residual Likelihood Forests (RLF).
EMPNet: Neural Localisation and Mapping Using Embedded Memory Points
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
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
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.
