Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Unsupervised Motion Representation Learning with Capsule Autoencoders
Authors: Ziwei Xu, Xudong Shen, Yongkang Wong, Mohan S. Kankanhalli
NeurIPS 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | MCAE is evaluated on a novel Trajectory20 motion dataset and various real-world skeleton-based human action datasets. Notably, it achieves better results than baselines on Trajectory20 with considerably fewer parameters and state-of-the-art performance on the unsupervised skeleton-based action recognition task. |
| Researcher Affiliation | Academia | Ziwei Xu , Xudong Shen , Yongkang Wong , Mohan S Kankanhalli School of Computing, National University of Singapore NUS Graduate School, National University of Singapore EMAIL EMAIL, EMAIL |
| Pseudocode | No | The paper describes the methodology in prose and mathematical equations but does not include any structured pseudocode or algorithm blocks. |
| Open Source Code | Yes | The source code and the T20 dataset of our research are accessible at https://github.com/Ziwei XU/Capsule Motion. |
| Open Datasets | Yes | We propose Trajectory20, a novel and challenging synthetic dataset with a wide class of motion patterns and controllable intra-class variations. ... The source code and the T20 dataset of our research are accessible at https://github.com/Ziwei XU/Capsule Motion. ... Three widely-used datasets are used for evaluation: NW-UCLA [48], NTU-RGBD60 (NTU60) [37], and NTU-RGBD120 (NTU120) [25]. |
| Dataset Splits | Yes | The training data is generated on-the-fly and a fixed test set of 10,000 samples is used for evaluation. ... For NTU60, we follow the official data split for the cross-subject (XSUB) and cross-view (XVIEW) protocols. The similar is implemented on NTU120 for the cross-subject (XSUB) and cross-setting (XSET) protocol. |
| Hardware Specification | Yes | The experiments are run on an NVIDIA Titan V GPU, where we use a batch size of 64, and the Adam [16] optimizer with a learning rate of 10 3. ... The computational work for this article was partially performed on resources of the National Supercomputing Centre, Singapore (https://www.nscc.sg). |
| Software Dependencies | No | The paper mentions using the Adam optimizer but does not specify version numbers for any programming languages, libraries, or other software dependencies. |
| Experiment Setup | Yes | We report the mean accuracy and standard error based on three runs with random initialization. The experiments are run on an NVIDIA Titan V GPU, where we use a batch size of 64, and the Adam [16] optimizer with a learning rate of 10 3. Please refer to the supplementary material for details. |