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Found 11 papers, 3 papers with code
From Heavy Rain Removal to Detail Restoration: A Faster and Better Network
Firstly, a dilated dense residual block (DDRB) within the rain streaks removal network is presented to aggregate high/low level features of heavy rain.
Modeling human intention inference in continuous 3D domains by inverse planning and body kinematics
We describe Generative Body Kinematics model, which predicts human intention inference in this domain using Bayesian inverse planning and inverse body kinematics.
Emergent Graphical Conventions in a Visual Communication Game
While recent studies of emergent communication primarily focus on symbolic languages, their settings overlook the graphical sketches existing in human communication; they do not account for the evolution process through which symbolic sign systems emerge in the trade-off between iconicity and symbolicity.
YouRefIt: Embodied Reference Understanding with Language and Gesture
To the best of our knowledge, this is the first embodied reference dataset that allows us to study referring expressions in daily physical scenes to understand referential behavior, human communication, and human-robot interaction.
Individual vs. Joint Perception: a Pragmatic Model of Pointing as Communicative Smithian Helping
We add another agent as a guide who can only help by marking an observation already perceived by the hunter with a pointing or not, without providing new observations or offering any instrumental help.
Modeling Communication to Coordinate Perspectives in Cooperation
We propose a computational account of overloaded signaling from a shared agency perspective which we call the Imagined We for Communication.
Learning Triadic Belief Dynamics in Nonverbal Communication from Videos
By aggregating different beliefs and true world states, our model essentially forms "five minds" during the interactions between two agents.
Joint Inference of States, Robot Knowledge, and Human (False-)Beliefs
Aiming to understand how human (false-)belief--a core socio-cognitive ability--would affect human interactions with robots, this paper proposes to adopt a graphical model to unify the representation of object states, robot knowledge, and human (false-)beliefs.
Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense
We demonstrate the power of this perspective to develop cognitive AI systems with humanlike common sense by showing how to observe and apply FPICU with little training data to solve a wide range of challenging tasks, including tool use, planning, utility inference, and social learning.
Measuring and modeling the perception of natural and unconstrained gaze in humans and machines
How accurate are humans in determining the gaze direction of others in lifelike scenes, when they can move their heads and eyes freely, and what are the sources of information for the underlying perceptual processes?
When Computer Vision Gazes at Cognition
(1) Human accuracy of discriminating targets 8{\deg}-10{\deg} of visual angle apart is around 40% in a free looking gaze task; (2) The ability to interpret gaze of different lookers vary dramatically; (3) This variance can be captured by the computational model; (4) Human outperforms the current model significantly.
