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06/07/2023
Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion
Instance segmentation in 3D is a challenging task due to the lack of lar...
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06/01/2023
Extracting Reward Functions from Diffusion Models
Diffusion models have achieved remarkable results in image generation, a...
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04/02/2023
Large Language Models are Few-shot Publication Scoopers
Driven by recent advances AI, we passengers are entering a golden age of...
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03/23/2023
Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition
To facilitate research in the direction of fine-tuning foundation models...
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11/28/2022
A Light Touch Approach to Teaching Transformers Multi-view Geometry
Transformers are powerful visual learners, in large part due to their co...
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11/25/2022
Pixels Together Strong: Segmenting Unknown Regions Rejected by All
Semantic segmentation methods typically perform per-pixel classification...
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09/24/2022
Learn what matters: cross-domain imitation learning with task-relevant embeddings
We study how an autonomous agent learns to perform a task from demonstra...
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07/20/2022
Illusionary Attacks on Sequential Decision Makers and Countermeasures
Autonomous intelligent agents deployed to the real-world need to be robu...
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06/13/2022
SNeS: Learning Probably Symmetric Neural Surfaces from Incomplete Data
We present a method for the accurate 3D reconstruction of partly-symmetr...
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03/31/2022
A 23 MW data centre is all you need
The field of machine learning has achieved striking progress in recent y...
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12/17/2021
Audio Retrieval with Natural Language Queries: A Benchmark Study
The objectives of this work are cross-modal text-audio and audio-text re...
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11/25/2021
Quantised Transforming Auto-Encoders: Achieving Equivariance to Arbitrary Transformations in Deep Networks
In this work we investigate how to achieve equivariance to input transfo...
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08/08/2021
Towards real-world navigation with deep differentiable planners
We train embodied neural networks to plan and navigate unseen complex 3D...
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07/20/2021
Learning Altruistic Behaviours in Reinforcement Learning without External Rewards
Can artificial agents learn to assist others in achieving their goals wi...
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05/05/2021
Moving SLAM: Fully Unsupervised Deep Learning in Non-Rigid Scenes
We propose a method to train deep networks to decompose videos into 3D g...
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05/05/2021
Audio Retrieval with Natural Language Queries
We consider the task of retrieving audio using free-form natural languag...
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03/31/2021
On the Origin of Species of Self-Supervised Learning
In the quiet backwaters of cs.CV, cs.LG and stat.ML, a cornucopia of new...
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11/22/2020
QuerYD: A video dataset with high-quality textual and audio narrations
We introduce QuerYD, a new large-scale dataset for retrieval and event l...
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03/31/2020
State-of-Art-Reviewing: A Radical Proposal to Improve Scientific Publication
Peer review forms the backbone of modern scientific manuscript evaluatio...
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03/09/2020
Multi-modal Self-Supervision from Generalized Data Transformations
Self-supervised learning has advanced rapidly, with several results beat...
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07/17/2018
Invariant Information Distillation for Unsupervised Image Segmentation and Clustering
We present a new method that learns to segment and cluster images withou...
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05/21/2018
Meta-learning with differentiable closed-form solvers
Adapting deep networks to new concepts from few examples is extremely ch...
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05/21/2018
Small steps and giant leaps: Minimal Newton solvers for Deep Learning
We propose a fast second-order method that can be used as a drop-in repl...
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04/01/2018
Substitute Teacher Networks: Learning with Almost No Supervision
Learning through experience is time-consuming, inefficient and often bad...
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03/26/2018
Long-term Tracking in the Wild: A Benchmark
We introduce a new video dataset and benchmark to assess single-object t...
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03/07/2017
Stopping GAN Violence: Generative Unadversarial Networks
While the costs of human violence have attracted a great deal of attenti...
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09/14/2016
Warped Convolutions: Efficient Invariance to Spatial Transformations
Convolutional Neural Networks (CNNs) are extremely efficient, since they...
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06/30/2016
Fully-Convolutional Siamese Networks for Object Tracking
The problem of arbitrary object tracking has traditionally been tackled ...
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06/16/2016
Learning feed-forward one-shot learners
One-shot learning is usually tackled by using generative models or discr...
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04/30/2014
