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Found 5 papers, 2 papers with code
Is Complexity Required for Neural Network Pruning? A Case Study on Global Magnitude Pruning
Surprisingly, we find that vanilla Global MP performs very well against the SOTA techniques.
Global Magnitude Pruning With Minimum Threshold Is All We Need
We showcase that magnitude based pruning, specifically, global magnitude pruning (GP) is sufficient to achieve SOTA performance on a range of neural network architectures.
Autonomous Aerial Cinematography In Unstructured Environments With Learned Artistic Decision-Making
In this work, we address the problem in its entirety and propose a complete system for real-time aerial cinematography that for the first time combines: (1) vision-based target estimation; (2) 3D signed-distance mapping for occlusion estimation; (3) efficient trajectory optimization for long time-horizon camera motion; and (4) learning-based artistic shot selection.
End-to-End Motion Planning of Quadrotors Using Deep Reinforcement Learning
In this work, a novel, end-to-end motion planning method is proposed for quadrotor navigation in cluttered environments.
Can a Robot Become a Movie Director? Learning Artistic Principles for Aerial Cinematography
Aerial filming is constantly gaining importance due to the recent advances in drone technology.
