Social LSTM: Human Trajectory Prediction in Crowded Spaces

al. in [32] use Inverse Reinforcement Learning to predict human paths in static scenes. They infer walkable paths in a scene by modeling human-space interactions. Walker et al. in [68] predict the behavior of generic agents (e.g., a ve-hicle) in a visual scene given a large collection of videos. Ziebart et al. [78,23] presented a planning based ...

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  Learning, Reinforcement, Inverse, Inverse reinforcement learning

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3D Reconstruction from Multiple Images

cvgl.stanford.edu

3.4 Multi View Stereo The Multi View Stereo algorithms are used to generate a dense 3D reconstruction of the object or scene. The techniques are usually based on the measurement of a consistency function, a function to measure whether \this 3D model is …

  Form, Multi, Multiple, Image, Reconstruction, View, Algorithm, Stereo, 3d reconstruction from multiple images, Multi view stereo, Multi view stereo algorithms

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Soft Actor-Critic: Off-Policy Maximum Entropy Deep ...

arxiv.org

Maximum entropy reinforcement learning optimizes poli-cies to maximize both the expected return and the ex-pected entropy of the policy. This framework has been used in many contexts, from inverse reinforcement learn-ing (Ziebart et al.,2008) to optimal control (Todorov,2008; Toussaint,2009;Rawlik et al.,2012). In guided policy

  Learning, Learn, Reinforcement, Inverse, Reinforcement learning, Inverse reinforcement learn ing

Chapter 2 Resource Masters - Math Problem Solving

jaeproblemsolving.weebly.com

©Glencoe/McGraw-Hill iv Glencoe Geometry Teacher’s Guide to Using the Chapter 2 Resource Masters The Fast FileChapter Resource system allows you to conveniently file the resources you use most often. The Chapter 2 Resource Mastersincludes the core materials needed for Chapter 2. These materials include worksheets, extensions, and assessment options.

  Geometry, Glencoe, Glencoe geometry

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