Cross-Domain 3D Model Retrieval via Visual Domain Adaption
Authors: Anan Liu, Shu Xiang, Wenhui Li, Weizhi Nie, Yuting Su
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | 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 liwenhui@tju.edu.cn |
| 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 fix λ=1, and µ=1. |