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04/04/2023
Learning to Name Classes for Vision and Language Models
Large scale vision and language models can achieve impressive zero-shot ...
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04/03/2023
Tunable Convolutions with Parametric Multi-Loss Optimization
Behavior of neural networks is irremediably determined by the specific l...
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11/16/2022
Region Proposal Network Pre-Training Helps Label-Efficient Object Detection
Self-supervised pre-training, based on the pretext task of instance disc...
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11/09/2022
Content-Diverse Comparisons improve IQA
Image quality assessment (IQA) forms a natural and often straightforward...
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10/07/2022
CLAD: A realistic Continual Learning benchmark for Autonomous Driving
In this paper we describe the design and the ideas motivating a new Cont...
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06/08/2022
Out-of-Distribution Detection with Class Ratio Estimation
Density-based Out-of-distribution (OOD) detection has recently been show...
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04/04/2022
Re-examining Distillation For Continual Object Detection
Training models continually to detect and classify objects, from new cla...
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03/23/2022
CroMo: Cross-Modal Learning for Monocular Depth Estimation
Learning-based depth estimation has witnessed recent progress in multipl...
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01/10/2022
Model-Based Image Signal Processors via Learnable Dictionaries
Digital cameras transform sensor RAW readings into RGB images by means o...
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12/13/2021
Long-tail Recognition via Compositional Knowledge Transfer
In this work, we introduce a novel strategy for long-tail recognition th...
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09/29/2021
Flow Based Models For Manifold Data
Flow-based generative models typically define a latent space with dimens...
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09/04/2021
On the Out-of-distribution Generalization of Probabilistic Image Modelling
Out-of-distribution (OOD) detection and lossless compression constitute ...
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06/18/2021
Residual Contrastive Learning for Joint Demosaicking and Denoising
The breakthrough of contrastive learning (CL) has fueled the recent succ...
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08/21/2020
Many-shot from Low-shot: Learning to Annotate using Mixed Supervision for Object Detection
Object detection has witnessed significant progress by relying on large,...
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03/31/2020
DeepLPF: Deep Local Parametric Filters for Image Enhancement
Digital artists often improve the aesthetic quality of digital photograp...
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02/28/2020
A Multi-Hypothesis Classification Approach to Color Constancy
Contemporary approaches frame the color constancy problem as learning ca...
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02/28/2020
A Multi-Hypothesis Approach to Color Constancy
Contemporary approaches frame the color constancy problem as learning ca...
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09/29/2019
SteReFo: Efficient Image Refocusing with Stereo Vision
Whether to attract viewer attention to a particular object, give the imp...
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11/28/2018
Meta-Learning for Few-shot Camera-Adaptive Color Constancy
Digital camera pipelines employ color constancy methods to estimate an u...
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07/19/2018
EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging without External Trackers
Ultrasound (US) is the most widely used fetal imaging technique. However...
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06/08/2018
Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents
We propose a fully automatic method to find standardized view planes in ...
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05/02/2018
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry
Pose estimation, i.e. predicting a 3D rigid transformation with respect ...
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04/11/2018
Attention U-Net: Learning Where to Look for the Pancreas
We propose a novel attention gate (AG) model for medical imaging that au...
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11/04/2017
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation
Deep learning approaches such as convolutional neural nets have consiste...
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09/19/2017
3D Reconstruction in Canonical Co-ordinate Space from Arbitrarily Oriented 2D Images
Limited capture range and the requirement to provide high quality initia...
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02/28/2017
Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging
3D Magnetic Resonance Imaging (MRI) is often a trade-off between fast bu...
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02/28/2017
