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Found 10 papers, 4 papers with code
EventEgo3D: 3D Human Motion Capture from Egocentric Event Streams
In response to the existing limitations, this paper 1) introduces a new problem, i. e., 3D human motion capture from an egocentric monocular event camera with a fisheye lens, and 2) proposes the first approach to it called EventEgo3D (EE3D).
3D Pose Estimation of Two Interacting Hands from a Monocular Event Camera
3D hand tracking from a monocular video is a very challenging problem due to hand interactions, occlusions, left-right hand ambiguity, and fast motion.
Relightable Neural Actor with Intrinsic Decomposition and Pose Control
Creating a digital human avatar that is relightable, drivable, and photorealistic is a challenging and important problem in Vision and Graphics.
Holoported Characters: Real-time Free-viewpoint Rendering of Humans from Sparse RGB Cameras
At inference, our method only requires four camera views of the moving actor and the respective 3D skeletal pose.
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.
Ranked #1 on
Egocentric Pose Estimation
on GlobalEgoMocap Test Dataset
(using extra training data)
Scene-Aware 3D Multi-Human Motion Capture from a Single Camera
In this work, we consider the problem of estimating the 3D position of multiple humans in a scene as well as their body shape and articulation from a single RGB video recorded with a static camera.
Scene-aware Egocentric 3D Human Pose Estimation
To this end, we propose an egocentric depth estimation network to predict the scene depth map from a wide-view egocentric fisheye camera while mitigating the occlusion of the human body with a depth-inpainting network.
Ranked #3 on
Egocentric Pose Estimation
on GlobalEgoMocap Test Dataset
(using extra training data)
HandFlow: Quantifying View-Dependent 3D Ambiguity in Two-Hand Reconstruction with Normalizing Flow
Through this, we demonstrate the quality of our probabilistic reconstruction and show that explicit ambiguity modeling is better-suited for this challenging problem.
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.
Ranked #4 on
Egocentric Pose Estimation
on GlobalEgoMocap Test Dataset
(using extra training data)
SSP-Net: Scalable Sequential Pyramid Networks for Real-Time 3D Human Pose Regression
In this paper we propose a highly scalable convolutional neural network, end-to-end trainable, for real-time 3D human pose regression from still RGB images.
Ranked #60 on
3D Human Pose Estimation
on MPI-INF-3DHP
