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Found 7 papers, 1 papers with code
Comparing Trajectory and Vision Modalities for Verb Representation
Given the importance of 3D space in formal models of verb semantics, we expect that these 2D images would result in impoverished representations that fail to capture nuanced differences in meaning.
Pretraining on Interactions for Learning Grounded Affordance Representations
Lexical semantics and cognitive science point to affordances (i. e. the actions that objects support) as critical for understanding and representing nouns and verbs.
Do Trajectories Encode Verb Meaning?
Distributional models learn representations of words from text, but are criticized for their lack of grounding, or the linking of text to the non-linguistic world.
A Visuospatial Dataset for Naturalistic Verb Learning
We introduce a new dataset for training and evaluating grounded language models.
Using Grounded Word Representations to Study Theories of Lexical Concepts
The fields of cognitive science and philosophy have proposed many different theories for how humans represent {``}concepts{''}.
Improving the Accuracy of the CogniLearn System for Cognitive Behavior Assessment
As a result of these improvements, the accuracy in recognizing cases where subjects touch their toes has gone from 76. 46% in our previous work to 97. 19% in this paper.
Enhanced Facial Recognition Framework based on Skin Tone and False Alarm Rejection
In this study, an enhanced face detection framework is proposed to improve detection rate based on skin color and provide a validation process.
