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Crowd-Driven Mapping, Localization and Planning
Navigation in dense crowds is a well-known open problem in robotics with...
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An Intelligent CNN-VAE Text Representation Technology Based on Text Semantics for Comprehensive Big Data
In the era of big data, a large number of text data generated by the Int...
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Mapping in a cycle: Sinkhorn regularized unsupervised learning for point cloud shapes
We propose an unsupervised learning framework with the pretext task of f...
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HDR-GAN: HDR Image Reconstruction from Multi-Exposed LDR Images with Large Motions
Synthesizing high dynamic range (HDR) images from multiple low-dynamic r...
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Recurrent Distillation based Crowd Counting
In recent years, with the progress of deep learning technologies, crowd ...
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Over-crowdedness Alert! Forecasting the Future Crowd Distribution
In recent years, vision-based crowd analysis has been studied extensivel...
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Learning Resilient Behaviors for Navigation Under Uncertainty Environments
Deep reinforcement learning has great potential to acquire complex, adap...
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Visualizing the Invisible: Occluded Vehicle Segmentation and Recovery
In this paper, we propose a novel iterative multi-task framework to comp...
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Enhancement Mask for Hippocampus Detection and Segmentation
Detection and segmentation of the hippocampal structures in volumetric b...
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Getting Robots Unfrozen and Unlost in Dense Pedestrian Crowds
We aim to enable a mobile robot to navigate through environments with de...
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Deformable Object Tracking with Gated Fusion
The tracking-by-detection framework receives growing attentions through ...
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An Intelligent Extraversion Analysis Scheme from Crowd Trajectories for Surveillance
In recent years, crowd analysis is important for applications such as sm...
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Fully Distributed Multi-Robot Collision Avoidance via Deep Reinforcement Learning for Safe and Efficient Navigation in Complex Scenarios
In this paper, we present a decentralized sensor-level collision avoidan...
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Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning
Developing a safe and efficient collision avoidance policy for multiple ...
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Deep-Learned Collision Avoidance Policy for Distributed Multi-Agent Navigation
High-speed, low-latency obstacle avoidance that is insensitive to sensor...
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Exemplar-AMMs: Recognizing Crowd Movements from Pedestrian Trajectories
In this paper, we present a novel method to recognize the types of crowd...
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Leveraging Long-Term Predictions and Online-Learning in Agent-based Multiple Person Tracking
We present a multiple-person tracking algorithm, based on combining part...
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