David Schneider

Orcid: 0000-0002-3272-2337

Affiliations:
  • Karlsruhe Institute of Technology, Germany


According to our database1, David Schneider authored at least 29 papers between 2021 and 2026.

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Bibliography

2026
IMPACT-Scribe: Interactive Temporal Action Segmentation with Boundary Scribbles and Query Planning.
CoRR, May, 2026

IMPACT-HOI: Supervisory Control for Onset-Anchored Partial HOI Event Construction.
CoRR, May, 2026

IMPACT-CYCLE: A Contract-Based Multi-Agent System for Claim-Level Supervisory Correction of Long-Video Semantic Memory.
CoRR, April, 2026

IMPACT: A Dataset for Multi-Granularity Human Procedural Action Understanding in Industrial Assembly.
CoRR, April, 2026

Mitigating Label Noise using Prompt-Based Hyperbolic Meta-Learning in Open-Set Domain Generalization.
Int. J. Comput. Vis., March, 2026

Scalable Video Action Anticipation with Cross Linear Attentive Memory.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2026

Privacy-Compliant Human Data Synthesis in Images for GDPR.
Proceedings of the 20th IEEE International Conference on Automatic Face and Gesture Recognition, 2026

2025
OmniFall: A Unified Staged-to-Wild Benchmark for Human Fall Detection.
CoRR, May, 2025

Exploring Self-supervised Skeleton-based Action Recognition in Occluded Environments.
Proceedings of the International Joint Conference on Neural Networks, 2025

2024
Learning human actions from complex manipulation tasks and their transfer to robots in the circular factory.
Autom., September, 2024

Rendering-Refined Stable Diffusion for Privacy Compliant Synthetic Data.
CoRR, 2024

Muscles in Time: Learning to Understand Human Motion by Simulating Muscle Activations.
CoRR, 2024

Masked Differential Privacy.
CoRR, 2024

Muscles in Time: Learning to Understand Human Motion In-Depth by Simulating Muscle Activations.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Towards Video-based Activated Muscle Group Estimation in the Wild.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

SynthAct: Towards Generalizable Human Action Recognition based on Synthetic Data.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Navigating Open Set Scenarios for Skeleton-Based Action Recognition.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Unveiling the Hidden Realm: Self-supervised Skeleton-based Action Recognition in Occluded Environments.
CoRR, 2023

FeatFSDA: Towards Few-shot Domain Adaptation for Video-based Activity Recognition.
CoRR, 2023

MuscleMap: Towards Video-based Activated Muscle Group Estimation.
CoRR, 2023

Anticipative Feature Fusion Transformer for Multi-Modal Action Anticipation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

2022
Is My Driver Observation Model Overconfident? Input-Guided Calibration Networks for Reliable and Interpretable Confidence Estimates.
IEEE Trans. Intell. Transp. Syst., 2022

Erfassung und Interpretation menschlicher Handlungen für die Programmierung von Robotern in der Produktion.
Autom., 2022

A Comparative Analysis of Decision-Level Fusion for Multimodal Driver Behaviour Understanding.
Proceedings of the 2022 IEEE Intelligent Vehicles Symposium, 2022

Multimodal Generation of Novel Action Appearances for Synthetic-to-Real Recognition of Activities of Daily Living.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

ModSelect: Automatic Modality Selection for Synthetic-to-Real Domain Generalization.
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

Pose-based Contrastive Learning for Domain Agnostic Activity Representations.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021
Let's Play for Action: Recognizing Activities of Daily Living by Learning from Life Simulation Video Games.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Affect-DML: Context-Aware One-Shot Recognition of Human Affect using Deep Metric Learning.
Proceedings of the 16th IEEE International Conference on Automatic Face and Gesture Recognition, 2021


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