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; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1]
Unsupervised Feature Learning for 3D Scene Reconstruction with Occupancy Maps
Authors: Vitor Guizilini, Fabio Ramos
AAAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments conducted in simulated and real large-scale datasets show a substantial gain in performance, while decreasing the amount of stored information by orders of magnitude without sacrificing accuracy. |
| Researcher Affiliation | Academia | Vitor Guizilini, Fabio Ramos School of Information Technologies, University of Sydney EMAIL |
| Pseudocode | Yes | Algorithm 1 ASK-Means initialization algorithm |
| Open Source Code | Yes | 1A C++ demo of the proposed algorithm is available in https: //bitbucket.org/vguizilini/cvpp |
| Open Datasets | Yes | In this section we validate the proposed algorithm using three different datasets: Room, a simulated indoor environment; Corridor, a real indoor environment; and Outdoor, a real outdoor environment2. ... 2Both real datasets were obtained from http://kos.informatik. uni-osnabrueck.de/3Dscans/ |
| Dataset Splits | No | The paper mentions 'different ratios of training/testing points' and 'every training/testing ratio' but does not provide specific percentages or counts for a fixed training/validation/test split. |
| Hardware Specification | No | The paper does not provide any specific hardware details such as GPU or CPU models used for running the experiments. |
| Software Dependencies | No | The paper mentions various algorithms and methods (e.g., K-means, Hilbert Maps, kd-tree) and cites their original papers, but it does not specify any software dependencies with version numbers (e.g., programming languages, libraries, or frameworks with their versions) used for implementation or experimentation. |
| Experiment Setup | Yes | In all experiments, ASK-means (Sec. ) was used with a threshold of 0.1% the maximum distance between points. ... Unoccupied points are generated by randomly sampling the beams that produced occupied points (a ratio of 1 point / 2 meters was used throughout the paper). |