Human Pose Estimation - Groups

LEMO

The dataset used in the paper is the LEMO dataset.

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EgoHumans dataset

The EgoHumans dataset consists of approximately 1 hour of video of up to 5 subjects performing highly dynamic activities.

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Campus and Shelf datasets

The Campus and Shelf datasets contain approximately 4000 frames of a single scene.

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CMU Panoptic Studio dataset

The CMU Panoptic Studio dataset is a large multi-view pose estimation dataset with several synchronized camera sequences of multiple interacting subjects.

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Sparse Inertial Poser

Sparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUs

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Pose

The Pose dataset is a subset of the Panoptic dataset, containing scenes with a single person and cameras.

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Maﬁa and Ultimatum

The Maﬁa and Ultimatum datasets are subsets of the Panoptic dataset, containing scenes with multiple people and cameras.

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Panoptic

The Panoptic dataset is a dense camera grid setup, capturing real video data of scenes with multiple people and cameras densely covering the viewing sphere.

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MEVADA

A fully automated system that estimates the camera intrinsics, the ground plane, and physical distances between people from a single RGB image or video.

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Microsoft COCO Keypoints

The Microsoft COCO Keypoints dataset is a large-scale benchmark for 2D human pose estimation and tracking in images.

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PandaNet: Anchor-based Single-Shot Multi-Person 3D Pose Estimation

PandaNet is a single-shot approach for multi-person 3D pose estimation that can handle images with a large number of people, strong occlusions, and varying sizes.

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AR Dataset

AR dataset is a dataset of images with a single or few people in the scene in common poses and 25K images with a single person in the scene performing fitness exercises.

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Human3D+

Human 3D pose estimation from a single image is a challenging task with numerous applications. Convolutional Neural Networks (CNNs) have recently achieved superior performance...

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Synthesizing Training Images for Boosting Human 3D Pose Estimation

Human 3D pose estimation from a single image is a challenging task with numerous applications. Convolutional Neural Networks (CNNs) have recently achieved superior performance...