Search Results for author:
Found 6 papers, 2 papers with code
Dessie: Disentanglement for Articulated 3D Horse Shape and Pose Estimation from Images
In recent years, 3D parametric animal models have been developed to aid in estimating 3D shape and pose from images and video.
CLHOP: Combined Audio-Video Learning for Horse 3D Pose and Shape Estimation
In the monocular setting, predicting 3D pose and shape of animals typically relies solely on visual information, which is highly under-constrained.
VAREN: Very Accurate and Realistic Equine Network
We introduce VAREN a novel 3D articulated parametric shape model learned from 3D scans of many real horses.
Human-Centric Autonomous Systems With LLMs for User Command Reasoning
The evolution of autonomous driving has made remarkable advancements in recent years, evolving into a tangible reality.
hSMAL: Detailed Horse Shape and Pose Reconstruction for Motion Pattern Recognition
In this paper we present our preliminary work on model-based behavioral analysis of horse motion.
[Re] Reimplementation of FixMatch and Investigation on Noisy (Pseudo) Labels and Confirmation Errors of FixMatch
FixMatch is a semi-supervised learning method, which achieves comparable results with fully supervised learning by leveraging a limited number of labeled data (pseudo labelling technique) and taking a good use of the unlabeled data (consistency regularization ).
