46 citations · 248 across the 39 of their papers we have counts for
7 papers · 1 filter
Revisiting the Master-Slave Architecture in Multi-Agent Deep Reinforcement Learning
Xiangyu Kong, Bo Xin, Fangchen Liu +1
Many tasks in artificial intelligence require the collaboration of multiple agents. We exam deep reinforcement learning for multi-agent domains. Recent research efforts often take…
RAN4IQA: Restorative Adversarial Nets for No-Reference Image Quality Assessment
Hongyu Ren, Diqi Chen, Yizhou Wang
Inspired by the free-energy brain theory, which implies that human visual system (HVS) tends to reduce uncertainty and restore perceptual details upon seeing a distorted image, we…
Zero-shot Learning via Shared-Reconstruction-Graph Pursuit
Bo Zhao, Xinwei Sun, Yuan Yao +1
Zero-shot learning (ZSL) aims to recognize objects from novel unseen classes without any training data. Recently, structure-transfer based methods are proposed to implement ZSL by…
AI Challenger : A Large-scale Dataset for Going Deeper in Image Understanding
Jiahong Wu, He Zheng, Bo Zhao +9
Significant progress has been achieved in Computer Vision by leveraging large-scale image datasets. However, large-scale datasets for complex Computer Vision tasks beyond classific…
GSplit LBI: Taming the Procedural Bias in Neuroimaging for Disease Prediction
Xinwei Sun, Lingjing Hu, Yuan Yao +1
In voxel-based neuroimage analysis, lesion features have been the main focus in disease prediction due to their interpretability with respect to the related diseases. However, we o…
End-to-end Active Object Tracking via Reinforcement Learning
Wenhan Luo, Peng Sun, Fangwei Zhong +3
We study active object tracking, where a tracker takes as input the visual observation (i.e., frame sequence) and produces the camera control signal (e.g., move forward, turn left,…