14 citations · 31 across the 8 of their papers we have counts for
9 papers
Unfolding Videos Dynamics via Taylor Expansion
Siyi Chen, Minkyu Choi, Zesen Zhao +3
Taking inspiration from physical motion, we present a new self-supervised dynamics learning strategy for videos: Video Time-Differentiation for Instance Discrimination (ViDiDi). Vi…
A Dual-Stream Neural Network Explains the Functional Segregation of Dorsal and Ventral Visual Pathways in Human Brains
Minkyu Choi, Kuan Han, Xiaokai Wang +2
The human visual system uses two parallel pathways for spatial processing and object recognition. In contrast, computer vision systems tend to use a single feedforward pathway, ren…
Human Eyes Inspired Recurrent Neural Networks are More Robust Against Adversarial Noises
Minkyu Choi, Yizhen Zhang, Kuan Han +2
Humans actively observe the visual surroundings by focusing on salient objects and ignoring trivial details. However, computer vision models based on convolutional neural networks…
Explainable Semantic Space by Grounding Language to Vision with Cross-Modal Contrastive Learning
Yizhen Zhang, Minkyu Choi, Kuan Han +1
In natural language processing, most models try to learn semantic representations merely from texts. The learned representations encode the distributional semantics but fail to con…
Generating Goal-Directed Visuomotor Plans Based on Learning Using a Predictive Coding-type Deep Visuomotor Recurrent Neural Network Model
Minkyu Choi, Takazumi Matsumoto, Minju Jung +1
The current paper presents how a predictive coding type deep recurrent neural networks can generate vision-based goal-directed plans based on prior learning experience by examining…
Predictive Coding for Dynamic Visual Processing: Development of Functional Hierarchy in a Multiple Spatio-Temporal Scales RNN Model
Minkyu Choi, Jun Tani
The current paper proposes a novel predictive coding type neural network model, the predictive multiple spatio-temporal scales recurrent neural network (P-MSTRNN). The P-MSTRNN lea…
Predictive Coding-based Deep Dynamic Neural Network for Visuomotor Learning
Jungsik Hwang, Jinhyung Kim, Ahmadreza Ahmadi +2
This study presents a dynamic neural network model based on the predictive coding framework for perceiving and predicting the dynamic visuo-proprioceptive patterns. In our previous…
Predictive Coding for Dynamic Vision : Development of Functional Hierarchy in a Multiple Spatio-Temporal Scales RNN Model
Minkyu Choi, Jun Tani
The current paper presents a novel recurrent neural network model, the predictive multiple spatio-temporal scales RNN (P-MSTRNN), which can generate as well as recognize dynamic vi…
Achieving Synergy in Cognitive Behavior of Humanoids via Deep Learning of Dynamic Visuo-Motor-Attentional Coordination
Jungsik Hwang, Minju Jung, Naveen Madapana +3
The current study examines how adequate coordination among different cognitive processes including visual recognition, attention switching, action preparation and generation can be…