A comprehensive survey on test-time adaptation under distribution shifts

J Liang, R He, T Tan - International Journal of Computer Vision, 2025‏ - Springer
Abstract Machine learning methods strive to acquire a robust model during the training
process that can effectively generalize to test samples, even in the presence of distribution …

Foundationpose: Unified 6d pose estimation and tracking of novel objects

B Wen, W Yang, J Kautz… - Proceedings of the IEEE …, 2024‏ - openaccess.thecvf.com
We present FoundationPose a unified foundation model for 6D object pose estimation and
tracking supporting both model-based and model-free setups. Our approach can be instantly …

Deep learning-based object pose estimation: A comprehensive survey

J Liu, W Sun, H Yang, Z Zeng, C Liu, J Zheng… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Object pose estimation is a fundamental computer vision problem with broad applications in
augmented reality and robotics. Over the past decade, deep learning models, due to their …

Mimicgen: A data generation system for scalable robot learning using human demonstrations

A Mandlekar, S Nasiriany, B Wen, I Akinola… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Imitation learning from a large set of human demonstrations has proved to be an effective
paradigm for building capable robot agents. However, the demonstrations can be extremely …

Instance-adaptive and geometric-aware keypoint learning for category-level 6d object pose estimation

X Lin, W Yang, Y Gao, T Zhang - Proceedings of the IEEE …, 2024‏ - openaccess.thecvf.com
Category-level 6D object pose estimation aims to estimate the rotation translation and size
of unseen instances within specific categories. In this area dense correspondence-based …

Handal: A dataset of real-world manipulable object categories with pose annotations, affordances, and reconstructions

A Guo, B Wen, J Yuan, J Tremblay… - 2023 IEEE/RSJ …, 2023‏ - ieeexplore.ieee.org
We present the HANDAL dataset for category-level object pose estimation and affordance
prediction. Unlike previous datasets, ours is focused on robotics-ready manipulable objects …

In search of lost online test-time adaptation: A survey

Z Wang, Y Luo, L Zheng, Z Chen, S Wang… - International Journal of …, 2024‏ - Springer
This article presents a comprehensive survey of online test-time adaptation (OTTA), focusing
on effectively adapting machine learning models to distributionally different target data upon …

Test-time adaptation against multi-modal reliability bias

M Yang, Y Li, C Zhang, P Hu, X Peng - The Twelfth International …, 2024‏ - openreview.net
Test-time adaptation (TTA) has emerged as a new paradigm for reconciling distribution shifts
across domains without accessing source data. However, existing TTA methods mainly …

Deep learning approaches for seizure video analysis: A review

D Ahmedt-Aristizabal, MA Armin, Z Hayder… - Epilepsy & Behavior, 2024‏ - Elsevier
Seizure events can manifest as transient disruptions in the control of movements which may
be organized in distinct behavioral sequences, accompanied or not by other observable …

[HTML][HTML] Test-time adaptation for 6D pose tracking

L Tian, C Oh, A Cavallaro - Pattern Recognition, 2024‏ - Elsevier
We propose a test-time adaptation for 6D object pose tracking that learns to adapt a pre-
trained model to track the 6D pose of novel objects. We consider the problem of 6D object …