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..
Cross-Domain 3D Model Retrieval via Visual Domain Adaption
Authors: Anan Liu, Shu Xiang, Wenhui Li, Weizhi Nie, Yuting Su
IJCAI 2018 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments on two popular datasets, under three designed cross-domain scenarios, demonstrate the superiority and effectiveness of the proposed method by comparing against the state-of-the-art methods. |
| Researcher Affiliation | Academia | School of Electrical and Information Engineering, Tianjin University, China EMAIL |
| Pseudocode | No | The paper describes the method using mathematical formulations and prose, but does not include any explicit pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link indicating that the source code for the described methodology is publicly available. |
| Open Datasets | Yes | Two popular 3D model datasets with diverse data distribution are utilized for evaluation... The National Taiwan University (NTU) 3D model dataset... [Chen et al., 2003]... Princeton Shape Benchmark (PSB)... [Shilane et al., 2004] |
| Dataset Splits | Yes | Additionally, the models in NTU and PSB are split into two subsets: training and test, with ratio 50% and 50% respectively. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., GPU models, CPU types) used for running the experiments. |
| Software Dependencies | No | The paper mentions architectures like Alex Net and MVCNN, but it does not provide specific software dependencies with version numbers (e.g., programming language versions, library versions, or framework versions). |
| Experiment Setup | Yes | MVCNN is trained on Model Net40... the output of fc7 (4096-D) is used as visual feature... We experimentally ๏ฌx ฮป=1, and ยต=1. |