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A comprehensive survey on test-time adaptation under distribution shifts
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 …
process that can effectively generalize to test samples, even in the presence of distribution …
Foundationpose: Unified 6d pose estimation and tracking of novel objects
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 …
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 …
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 …
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
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 …
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 …
prediction. Unlike previous datasets, ours is focused on robotics-ready manipulable objects …
In search of lost online test-time adaptation: A survey
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 …
on effectively adapting machine learning models to distributionally different target data upon …
Test-time adaptation against multi-modal reliability bias
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 …
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 …
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 …
trained model to track the 6D pose of novel objects. We consider the problem of 6D object …