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Learning to Sample the Most Useful Training Patches from Images
Some image restoration tasks like demosaicing require difficult training...
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Class-Agnostic Segmentation Loss and Its Application to Salient Object Detection and Segmentation
In this paper we present a novel loss function, called class-agnostic se...
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Diagnosing and Preventing Instabilities in Recurrent Video Processing
Recurrent models are becoming a popular choice for video enhancement tas...
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HOTA: A Higher Order Metric for Evaluating Multi-Object Tracking
Multi-Object Tracking (MOT) has been notoriously difficult to evaluate. ...
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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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Simulation-Based Inference for Global Health Decisions
The COVID-19 pandemic has highlighted the importance of in-silico epidem...
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Deep Multi-Agent Reinforcement Learning for Decentralized Continuous Cooperative Control
Deep multi-agent reinforcement learning (MARL) holds the promise of auto...
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Using Hindsight to Anchor Past Knowledge in Continual Learning
In continual learning, the learner faces a stream of data whose distribu...
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Global Texture Enhancement for Fake Face Detection in the Wild
Generative Adversarial Networks (GANs) can generate realistic fake face ...
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Domain-invariant Stereo Matching Networks
State-of-the-art stereo matching networks have difficulties in generaliz...
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Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
Probabilistic programming languages (PPLs) are receiving widespread atte...
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Let's Take This Online: Adapting Scene Coordinate Regression Network Predictions for Online RGB-D Camera Relocalisation
Many applications require a camera to be relocalised online, without exp...
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Res2Net: A New Multi-scale Backbone Architecture
Representing features at multiple scales is of great importance for nume...
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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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Learning Arbitrary Pairwise Potentials in CRFs for Semantic Segmentation
Are we using the right potential functions in the Conditional Random Fie...
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Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation
We consider the task of learning a classifier for semantic segmentation ...
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Online Real-time Multiple Spatiotemporal Action Localisation and Prediction
We present a deep-learning framework for real-time multiple spatio-tempo...
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Deeply supervised salient object detection with short connections
Recent progress on saliency detection is substantial, benefiting mostly ...
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Learning to Navigate the Energy Landscape
In this paper, we present a novel and efficient architecture for address...
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Joint Object-Material Category Segmentation from Audio-Visual Cues
It is not always possible to recognise objects and infer material proper...
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Staple: Complementary Learners for Real-Time Tracking
Correlation Filter-based trackers have recently achieved excellent perfo...
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Prototypical Priors: From Improving Classification to Zero-Shot Learning
Recent works on zero-shot learning make use of side information such as ...
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Efficient Semidefinite Branch-and-Cut for MAP-MRF Inference
We propose a Branch-and-Cut (B&C) method for solving general MAP-MRF inf...
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ImageSpirit: Verbal Guided Image Parsing
Humans describe images in terms of nouns and adjectives while algorithms...
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