DreamCatcher: A Wearer-aware Multi-modal Sleep Event Dataset Based on Earables in Non-restrictive Environments
No confident code implementation found for this paper. 3 possible matches can be shown below.
No confident code implementation found for this paper. 3 possible matches can be shown below.
No confident code match yet
We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 3 weaker matches are hidden by default — verify before relying on them.
No code implementations found yet.
Know of an implementation? Let us know in the comments below!
M3DBench: Towards Omni 3D Assistant with Interleaved Multi-modal Instructions
EgoSim: Egocentric Exploration in Virtual Worlds with Multi-modal Conditioning
Hierarchical Adaptive Value Estimation for Multi-modal Visual Reinforcement Learning
Super Deep Contrastive Information Bottleneck for Multi-modal Clustering
An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions
Cross-modal Representation Flattening for Multi-modal Domain Generalization
@article{wang2026dreamcatcher,
title = {DreamCatcher: A Wearer-aware Multi-modal Sleep Event Dataset Based on Earables in Non-restrictive Environments},
author = {Zeyu Wang and Xiyuxing Zhang and Ruotong Yu and Yuntao Wang and Kenneth Christofferson and Jingru Zhang and Alex Mariakakis and Yuanchun Shi},
year = {2026},
url = {https://www.semanticscholar.org/paper/4a78db49de056f172ad8f8b6a803115c3bb15c50},
journal = {NEURIPS 2024 2024}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/4a78db49de056f172ad8f8b6a803115c3bb15c50)