MovieQA_CVPR2016
Movie QA system
This project explores question-answering in movies using various machine learning approaches.
Contains approaches introduced in the MovieQA benchmark dataset paper
80 stars
5 watching
31 forks
Language: Python
last commit: almost 10 years agoRelated projects:
| Repository | Description | Stars |
|---|---|---|
 simmerchan/kg-demo-for-movie | A knowledge graph-based question answering system for movies | 1,293 |
 maluuba/newsqa | Compiles and provides structured access to Maluuba's NewsQA dataset for natural language question answering research. | 253 |
 lupantech/scienceqa | A dataset and software framework for building multimodal reasoning systems to answer science questions. | 615 |
 microsoft/pica | An empirical study on using GPT-3 for multimodal question answering tasks with few-shot learning. | 85 |
 milvlg/prophet | An implementation of a two-stage framework designed to prompt large language models with answer heuristics for knowledge-based visual question answering tasks. | 270 |
 hwchase17/notion-qa | A Python-based question answering system built on top of Notion's database and OpenAI's API for natural language processing. | 2,139 |
 ailab-cvc/seed-bench | A benchmark for evaluating large language models' ability to process multimodal input | 322 |
 jayleicn/tvqa | PyTorch implementation of video question answering system based on TVQA dataset | 172 |
 markdtw/vqa-winner-cvprw-2017 | Implementations and tools for training and fine-tuning a visual question answering model based on the 2017 CVPR workshop winner's approach. | 164 |
 mohamedadaly/labr | A dataset of Arabic book reviews for natural language processing tasks | 44 |
 mlpc-ucsd/bliva | A multimodal LLM designed to handle text-rich visual questions | 270 |
 noagarcia/roll-videoqa | A PyTorch-based model for answering questions about videos based on unseen scenes and storylines | 19 |
 cadene/vqa.pytorch | A PyTorch implementation of visual question answering with multimodal representation learning | 718 |
 jnhwkim/nips-mrn-vqa | This project presents a neural network model designed to answer visual questions by combining question and image features in a residual learning framework. | 39 |
 cmmmu-benchmark/cmmmu | A benchmark for evaluating the performance of multimodal question answering models on diverse domains and data types | 46 |