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Found 6 papers, 6 papers with code
Do Pedestrians Pay Attention? Eye Contact Detection in the Wild
In urban or crowded environments, humans rely on eye contact for fast and efficient communication with nearby people.
OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association
We present a generic neural network architecture that uses Composite Fields to detect and construct a spatio-temporal pose which is a single, connected graph whose nodes are the semantic keypoints (e. g., a person's body joints) in multiple frames.
Ranked #2 on
Car Pose Estimation
on ApolloCar3D
Perceiving Humans: from Monocular 3D Localization to Social Distancing
Our neural network estimates human 3D body locations and their orientation with a measure of uncertainty.
MonStereo: When Monocular and Stereo Meet at the Tail of 3D Human Localization
Monocular and stereo visions are cost-effective solutions for 3D human localization in the context of self-driving cars or social robots.
MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation
We tackle the fundamentally ill-posed problem of 3D human localization from monocular RGB images.
PifPaf: Composite Fields for Human Pose Estimation
We propose a new bottom-up method for multi-person 2D human pose estimation that is particularly well suited for urban mobility such as self-driving cars and delivery robots.
Ranked #10 on
Keypoint Detection
on COCO test-dev
