Egocentric Pose Estimation
7 papers with code • 4 benchmarks • 6 datasets
Benchmarks
These leaderboards are used to track progress in Egocentric Pose Estimation
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KITTI
xR-EgoPose
UnrealEgo
SceneEgo
Latest papers with no code
A Survey on 3D Egocentric Human Pose Estimation
Egocentric human pose estimation aims to estimate human body poses and develop body representations from a first-person camera perspective.
EgoPoseFormer: A Simple Baseline for Egocentric 3D Human Pose Estimation
We also show that our method can be seamlessly extended to monocular settings, which achieves state-of-the-art performance on the SceneEgo dataset, improving MPJPE by 25. 5mm (21% improvement) compared to the best existing method with only 60. 7% model parameters and 36. 4% FLOPs.
Real-Time Simulated Avatar from Head-Mounted Sensors
We present SimXR, a method for controlling a simulated avatar from information (headset pose and cameras) obtained from AR / VR headsets.
SimpleEgo: Predicting Probabilistic Body Pose from Egocentric Cameras
This presents a challenging scenario, as parts of the body often fall outside of the image or are occluded.
Egocentric Whole-Body Motion Capture with FisheyeViT and Diffusion-Based Motion Refinement
In this work, we explore egocentric whole-body motion capture using a single fisheye camera, which simultaneously estimates human body and hand motion.
UnrealEgo: A New Dataset for Robust Egocentric 3D Human Motion Capture
We present UnrealEgo, i. e., a new large-scale naturalistic dataset for egocentric 3D human pose estimation.
Estimating Egocentric 3D Human Pose in the Wild with External Weak Supervision
Specifically, we first generate pseudo labels for the EgoPW dataset with a spatio-temporal optimization method by incorporating the external-view supervision.
Egocentric Pose Estimation from Human Vision Span
Existing approaches either use a narrow field of view front facing camera that barely captures the wearer, or an extruded head-mounted top-down camera for maximal wearer visibility.
xR-EgoPose: Egocentric 3D Human Pose from an HMD Camera
Our quantitative evaluation, both on synthetic and real-world datasets, shows that our strategy leads to substantial improvements in accuracy over state of the art egocentric pose estimation approaches.
Mo2Cap2: Real-time Mobile 3D Motion Capture with a Cap-mounted Fisheye Camera
We tackle these challenges based on a novel lightweight setup that converts a standard baseball cap to a device for high-quality pose estimation based on a single cap-mounted fisheye camera.
