no code implementations • 13 Dec 2023 • Yuanbo Wen, Tao Gao, ZiQi Li, Jing Zhang, Ting Chen
Haze obscures remote sensing images, hindering valuable information extraction.
no code implementations • ICCV 2023 • YuFei Wang, Bo Li, Ge Zhang, Qi Liu, Tao Gao, Yuchao Dai
Existing deep learning-based depth completion methods generally employ massive stacked layers to predict the dense depth map from sparse input data.
1 code implementation • 19 Sep 2023 • Yuanbo Wen, Tao Gao, ZiQi Li, Jing Zhang, Ting Chen
This module leverages dimension-wise queries that are independent of the input features and employs global context-aware attention (GCA) to capture essential features while avoiding the entanglement of redundant or irrelevant information.
1 code implementation • 6 Apr 2023 • Tao Gao, Yuanbo Wen, Kaihao Zhang, Peng Cheng, Ting Chen
Rain-by-snow weather removal is a specialized task in weather-degraded image restoration aiming to eliminate coexisting rain streaks and snow particles.
1 code implementation • 7 May 2022 • Yuanbo Wen, Tao Gao, Jing Zhang, Kaihao Zhang, Ting Chen
This approach comprises two key modules, a rain streaks removal network (R$^2$Net) focusing on accurate rain removal, and a details reconstruction network (DRNet) designed to recover the textural details of rain-free images.
no code implementations • 2 Dec 2021 • Yingdong Qian, Marta Kryven, Tao Gao, Hanbyul Joo, Josh Tenenbaum
We describe Generative Body Kinematics model, which predicts human intention inference in this domain using Bayesian inverse planning and inverse body kinematics.
no code implementations • 28 Nov 2021 • Shuwen Qiu, Sirui Xie, Lifeng Fan, Tao Gao, Jungseock Joo, Song-Chun Zhu, Yixin Zhu
Humans communicate with graphical sketches apart from symbolic languages.
no code implementations • ICCV 2021 • Yixin Chen, Qing Li, Deqian Kong, Yik Lun Kei, Song-Chun Zhu, Tao Gao, Yixin Zhu, Siyuan Huang
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.
no code implementations • 3 Jun 2021 • Stephanie Stacy, Chenfei Li, Minglu Zhao, Yiling Yun, Qingyi Zhao, Max Kleiman-Weiner, Tao Gao
We propose a computational account of overloaded signaling from a shared agency perspective which we call the Imagined We for Communication.
no code implementations • 3 Jun 2021 • Kaiwen Jiang, Stephanie Stacy, Chuyu Wei, Adelpha Chan, Federico Rossano, Yixin Zhu, Tao Gao
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.
1 code implementation • CVPR 2021 • Lifeng Fan, Shuwen Qiu, Zilong Zheng, Tao Gao, Song-Chun Zhu, Yixin Zhu
By aggregating different beliefs and true world states, our model essentially forms "five minds" during the interactions between two agents.
no code implementations • 25 Apr 2020 • Tao Yuan, Hangxin Liu, Lifeng Fan, Zilong Zheng, Tao Gao, Yixin Zhu, Song-Chun Zhu
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.
no code implementations • 20 Apr 2020 • Yixin Zhu, Tao Gao, Lifeng Fan, Siyuan Huang, Mark Edmonds, Hangxin Liu, Feng Gao, Chi Zhang, Siyuan Qi, Ying Nian Wu, Joshua B. Tenenbaum, Song-Chun Zhu
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.
no code implementations • 29 Nov 2016 • Daniel Harari, Tao Gao, Nancy Kanwisher, Joshua Tenenbaum, Shimon Ullman
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?
1 code implementation • 8 Dec 2014 • Tao Gao, Daniel Harari, Joshua Tenenbaum, Shimon Ullman
(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.