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Found 6 papers, 4 papers with code
ChatPose: Chatting about 3D Human Pose
Additionally, ChatPose empowers LLMs to apply their extensive world knowledge in reasoning about human poses, leading to two advanced tasks: speculative pose generation and reasoning about pose estimation.
POCO: 3D Pose and Shape Estimation with Confidence
To address this, we develop POCO, a novel framework for training HPS regressors to estimate not only a 3D human body, but also their confidence, in a single feed-forward pass.
Detecting Human-Object Contact in Images
To build HOT, we use two data sources: (1) We use the PROX dataset of 3D human meshes moving in 3D scenes, and automatically annotate 2D image areas for contact via 3D mesh proximity and projection.
Learning to Regress Bodies from Images using Differentiable Semantic Rendering
For Minimally-Clothed regions, we define the DSR-MC loss, which encourages a tight match between a rendered SMPL body and the minimally-clothed regions of the image.
Ranked #51 on
3D Human Pose Estimation
on 3DPW
(using extra training data)
ProtoGAN: Towards Few Shot Learning for Action Recognition
To the best of our knowledge, we are the first to report the results for G-FSL and provide a strong benchmark for future research.
Progression Modelling for Online and Early Gesture Detection
Online and Early detection of gestures is crucial for building touchless gesture based interfaces.
