Looking at Mondrian's Victory Boogie-Woogie: What Do I Feel?
Authors: Andreza Sartori, Yan Yan, Gözde özbal, Alkim Almila Akdag Salah, Albert Ali Salah, Nicu Sebe
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | To this end, we employ computer vision and sentiment analysis to learn statistical patterns associated with positive and negative emotions on abstract paintings. We propose a multimodal approach which combines both visual and metadata features in order to improve the machine performance. ... We apply our multimodal approach on two datasets of abstract paintings: (1) a collection of professional paintings from the MART Museum and (2) a collection of amateur paintings from deviant Art (dA), an online social network site designed to user-generated art. |
| Researcher Affiliation | Collaboration | Andreza Sartori DISI, University of Trento Telecom Italia SKIL Lab Trento, Italy andreza.sartori@disi.unitn.it Yan Yan DISI, University of Trento, Italy ADSC, UIUC, Singapore yan@disi.unitn.it G ozde Ozbal Fondazione Bruno Kessler Trento, Italy gozbalde@gmail.com Alkim Almila Akda g Salah KNAW, e-Humanities Group Amsterdam, the Netherlands alelma@ucla.edu Albert Ali Salah Bo gazic i University Istanbul, Turkey salah@boun.edu.tr Nicu Sebe DISI, University of Trento Trento, Italy sebe@disi.unitn.it |
| Pseudocode | Yes | Algorithm 1: An efficient iterative algorithm to solve the optimization problem in Eq.(4). |
| Open Source Code | No | The paper states: 'The datasets with their respective ground truths are publicly available at: http://disi.unitn.it/ sartori/datasets/' but does not provide a link or statement indicating the open-source release of the code for the described methodology. |
| Open Datasets | Yes | The datasets with their respective ground truths are publicly available at: http://disi.unitn.it/ sartori/datasets/ |
| Dataset Splits | Yes | To test the approach, a 5-fold cross-validation setup is used, where the images are assigned to folds randomly." and "5-fold cross-validations are used in all experiments and the best performance is reported. |
| Hardware Specification | No | The paper does not provide any specific hardware details (e.g., CPU, GPU models, memory, or cloud instance types) used for running the experiments. |
| Software Dependencies | No | The paper mentions several software components like 'Stanford Parser', 'Word Net', 'Senti Words', 'Multi Word Net', 'Senti Word Net', and 'Text Pro', but does not provide specific version numbers for any of them. |
| Experiment Setup | Yes | For the late fusion with the weighted linear combination strategy, the weight a is tuned within the range {0.1, 0.2, 0.3, ..., 1}. For the joint flexible Schatten p-norm model, the parameters λ1 and λ2 are tuned within the range {10 3, 10 2, ..., 103} and p is tuned within the range {0.01, 0.05, 0.1, 0.2, 0.5, 0.8, 1}. |