Leaving Flatland: Advances in 3D behavioral measurement

2021-12-03 · Jesse D. Marshall, Tianqing Li, Joshua H. Wu, Timothy W. Dunn

Animals move in three dimensions (3D). Thus, 3D measurement is necessary to report the true kinematics of animal movement. Existing 3D measurement techniques draw on specialized hardware, such as motion capture or depth cameras, as well as deep multi-view and monocular computer vision. Continued advances at the intersection of deep learning and computer vision will facilitate 3D tracking across more anatomical features, with less training data, in additional species, and within more natural, occlusive environments. 3D behavioral measurement enables unique applications in phenotyping, investigating the neural basis of behavior, and designing artificial agents capable of imitating animal behavior.

📄 PDF Abstract BibTeX arXiv:2112.01987

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Flatland: a Lightweight First-Person 2-D Environment for Reinforcement Learning

2018-09-03 · Hugo Caselles-Dupré, Louis Annabi, Oksana Hagen, Michael Garcia-Ortiz 외

Flatland is a simple, lightweight environment for fast prototyping and testing of reinforcement learning agents. It is of lower complexity compared to similar 3D platforms (e.g. DeepMind Lab or VizDoom), but emulates phy…

Lifelong learning reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Flatland-RL : Multi-Agent Reinforcement Learning on Trains

2020-12-10 · Sharada Mohanty, Erik Nygren, Florian Laurent, Manuel Schneider 외

Efficient automated scheduling of trains remains a major challenge for modern railway systems. The underlying vehicle rescheduling problem (VRSP) has been a major focus of Operations Research (OR) since decades. Traditio…

Imitation Learning Multi-agent Reinforcement Learning reinforcement-learning Reinforcement Learning+2

Bitbox: Behavioral Imaging Toolbox for Computational Analysis of Behavior from Videos

2025-12-19 · Evangelos Sariyanidi, Gokul Nair, Lisa Yankowitz, Casey J. Zampella 외 arxiv

Computational measurement of human behavior from video has recently become feasible due to major advances in AI. These advances now enable granular and precise quantification of facial expression, head movement, body act…

3DoF Localization from a Single Image and an Object Map: the Flatlandia Problem and Dataset

2023-04-13 · Matteo Toso, Matteo Taiana, Stuart James, Alessio Del Bue

Efficient visual localization is crucial to many applications, such as large-scale deployment of autonomous agents and augmented reality. Traditional visual localization, while achieving remarkable accuracy, relies on ex…

Privacy Preserving Visual Localization

FlatLands: Generative Floormap Completion From a Single Egocentric View

2026-03-16 · Subhransu S. Bhattacharjee, Dylan Campbell, Rahul Shome arxiv

A single egocentric image typically captures only a small portion of the floor, yet a complete metric traversability map of the surroundings would better serve applications such as indoor navigation. We introduce FlatLan…