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Found 6 papers, 3 papers with code
U3DS$^3$: Unsupervised 3D Semantic Scene Segmentation
To achieve this, U3DS$^3$ leverages a generalized unsupervised segmentation method for both object and background across both indoor and outdoor static 3D point clouds with no requirement for model pre-training, by leveraging only the inherent information of the point cloud to achieve full 3D scene segmentation.
SignAvatars: A Large-scale 3D Sign Language Holistic Motion Dataset and Benchmark
We present SignAvatars, the first large-scale, multi-prompt 3D sign language (SL) motion dataset designed to bridge the communication gap for Deaf and hard-of-hearing individuals.
Decomposed Human Motion Prior for Video Pose Estimation via Adversarial Training
Estimating human pose from video is a task that receives considerable attention due to its applicability in numerous 3D fields.
Ranked #60 on
3D Human Pose Estimation
on 3DPW
(PA-MPJPE metric)
ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction
Our method significantly outperforms the best interacting-hand approaches on the InterHand2. 6M dataset while yielding comparable performance with the state-of-the-art single-hand methods on the FreiHand dataset.
Ranked #2 on
3D Interacting Hand Pose Estimation
on InterHand2.6M
RangeUDF: Semantic Surface Reconstruction from 3D Point Clouds
We present RangeUDF, a new implicit representation based framework to recover the geometry and semantics of continuous 3D scene surfaces from point clouds.
P2-Net: Joint Description and Detection of Local Features for Pixel and Point Matching
Accurately describing and detecting 2D and 3D keypoints is crucial to establishing correspondences across images and point clouds.
