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 [1].
Micro-macro Wavelet-based Gaussian Splatting for 3D Reconstruction from Unconstrained Images
Authors: Yihui Li, Chengxin Lv, Hongyu Yang, Di Huang
AAAI 2025 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments demonstrate that MW-GS delivers state-of-the-art rendering performance, surpassing existing methods. |
| Researcher Affiliation | Academia | 1 State Key Laboratory of Complex and Critical Software Environment, Beijing, China 2 School of Computer Science and Engineering, Beihang University, China 3 School of Artificial Intelligence, Beihang University, China 4 Shanghai Artificial Intelligence Laboratory, Shanghai, China EMAIL |
| Pseudocode | No | The paper describes the method using prose and mathematical formulas, without explicitly labeled pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not contain any explicit statements about releasing source code, nor does it provide a link to a code repository. |
| Open Datasets | Yes | Following previous works (Chen et al. 2022b; Zhang et al. 2024), we evaluate different methods on three datasets: Brandenburg Gate, Sacre Coeur, and Trevi Fountain |
| Dataset Splits | No | The paper states 'with all images downsampled by a factor of 2 during both training and evaluation' but does not specify the training/validation/test splits, percentages, or sample counts for the datasets used. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., exact GPU/CPU models, processor types, or memory amounts) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details, such as library or solver names with version numbers. |
| Experiment Setup | No | The paper does not contain specific experimental setup details such as concrete hyperparameter values, training configurations, or system-level settings in the main text. |