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Learning from disagreement: A survey
Abstract Many tasks in Natural Language Processing (NLP) and Computer Vision (CV) offer
evidence that humans disagree, from objective tasks such as part-of-speech tagging to more …
evidence that humans disagree, from objective tasks such as part-of-speech tagging to more …
Overcoming limitations of mixture density networks: A sampling and fitting framework for multimodal future prediction
Future prediction is a fundamental principle of intelligence that helps plan actions and avoid
possible dangers. As the future is uncertain to a large extent, modeling the uncertainty and …
possible dangers. As the future is uncertain to a large extent, modeling the uncertainty and …
Contactdb: Analyzing and predicting grasp contact via thermal imaging
Gras** and manipulating objects is an important human skill. Since hand-object contact is
fundamental to gras**, capturing it can lead to important insights. However, observing …
fundamental to gras**, capturing it can lead to important insights. However, observing …
Eliciting and learning with soft labels from every annotator
The labels used to train machine learning (ML) models are of paramount importance.
Typically for ML classification tasks, datasets contain hard labels, yet learning using soft …
Typically for ML classification tasks, datasets contain hard labels, yet learning using soft …
SemEval-2021 task 12: Learning with disagreements
Disagreement between coders is ubiquitous in virtually all datasets annotated with human
judgements in both natural language processing and computer vision. However, most …
judgements in both natural language processing and computer vision. However, most …
Deep-panther: Learning-based perception-aware trajectory planner in dynamic environments
J Tordesillas, JP How - IEEE Robotics and Automation Letters, 2023 - ieeexplore.ieee.org
This letter presents Deep-PANTHER, a learning-based perception-aware trajectory planner
for unmanned aerial vehicles (UAVs) in dynamic environments. Given the current state of the …
for unmanned aerial vehicles (UAVs) in dynamic environments. Given the current state of the …
Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealing
Abstract We introduce Annealed Multiple Choice Learning (aMCL) which combines
simulated annealing with MCL. MCL is a learning framework handling ambiguous tasks by …
simulated annealing with MCL. MCL is a learning framework handling ambiguous tasks by …
Iteratively applying neural networks to automatically identify pixels of salient objects portrayed in digital images
The present disclosure relates to systems, method, and computer readable media that
iteratively apply a neural network to a digital image at a reduced resolution to auto matically …
iteratively apply a neural network to a digital image at a reduced resolution to auto matically …
Utilizing interactive deep learning to select objects in digital visual media
US11568627B2 - Utilizing interactive deep learning to select objects in digital visual media
- Google Patents US11568627B2 - Utilizing interactive deep learning to select objects in …
- Google Patents US11568627B2 - Utilizing interactive deep learning to select objects in …
The visual centrifuge: Model-free layered video representations
JB Alayrac, J Carreira… - Proceedings of the IEEE …, 2019 - openaccess.thecvf.com
True video understanding requires making sense of non-lambertian scenes where the color
of light arriving at the camera sensor encodes information about not just the last object it …
of light arriving at the camera sensor encodes information about not just the last object it …