Dataset

This is an unofficial host for the MovieNet dataset.Refer to the official project repo for more details (data format, license, etc.).

  Usage

Combine the split files into a large zip: cat frames_part_* > frames.zip.

P.S. I host this repo for easier public access to the original large MovieNet dataset, since the official website has problems for years.If the authors find it an infringement of rights, plz contact me for deletion.

MovieNet-PS is a dataset for person search in movie data.

Check our GitHub repo for details.Thanks to MovieNet, which is the source of raw data.

  Terms of Use

By downloading the dataset, you agree to the following terms:

You will use the data only for non-commercial research and educational purposes.

  Overall Information





  Introduction

'./Image': Images collected from the MovieNet dataset. './annotation/Images.mat': 1 * 736,835 struct (736,835… See the full description on the dataset page: https://huggingface.co/datasets/ZhengPeng7/MovieNet-PS.

Movienet: a novel deep learning approach for 4D MRI reconstruction that exploits space-time-coil correlations and motion preservation instead of k-space data consistency to accelerate the acquisition of golden-angle radial data and enable sub-second reconstruction times in dynamic MRI.

Main Python code located at: https://github.com/victor-murray/Movienet.

Please, use this citation: Murray V, Siddiq S, Crane C, El Homsi M, Kim T, Wu C, Otazo R. Movienet: Deep space-time-coil reconstruction network without k-space data consistency for fast motion-resolved 4D MRI. Magn Reson Med. 2024; 91: 600–614. doi: 10.1002/mrm.29892

DOI: https://doi.org/10.1002/mrm.29892

This is the LRMovieNet dataset proposed by ECCV 2024 Paper "Multimodal Label Relevance Ranking via Reinforcement Learning". The code is available at https://github.com/ChazzyGordon/LR2PPO. Please go to Files and versions to download the LRMovieNet dataset. We select 3,206 clips from 219 videos in the MovieNet dataset. For each movie clip, we extract frames from the video and input them into the RAM model to obtain image labels. Concurrently, we input the descriptions of each movie clip into… See the full description on the dataset page: https://huggingface.co/datasets/ChazzyGordon/LRMovieNet.

VITA-MLLM/MovieNet-Summary dataset hosted on Hugging Face and contributed by the HF Datasets community

HD-Movienet enables accelerated 3D radial k-space acquisition for motion-resolved 4D MRI of the lungs. It achieves an isotropic resolution of 1.1 × 1.1 × 1.1 mm³, with scan times of 2 minutes for anatomical imaging at both expiration and inspiration, encompassing 4 respiratory phases.

This file is for a 3D HD-Movienet model state dictionary for 4 motion states.

Main Python code located at: https://github.com/victor-murray/HD-Movienet.

Please, use this citation: Murray V, Wu C, Otazo R. High-definition motion-resolved MRI using 3D radial kooshball acquisition and deep learning spatial-temporal 4D reconstruction. Phys Med Biol. 2025 Jun 17;70(12). doi: 10.1088/1361-6560/ade195. PMID: 40472864.

DOI: https://doi.org/10.1088/1361-6560/ade195

MoviePuzzle Dataset

  Introduce

This dataset is based on MovieNet for MoviePuzzle task. We use 228 movie to generate 10031 movie clips. 7048 clips for train, 589 for val, 1178 for in domain test and 1196 for out domain test.

  Download

You can download the full dataset here: https://movienet.github.io/

  Structure

We categorized a dataset of 10031 movie clips into labels ranging from 0 to 10030. Then, we divided this dataset into four subsets: the training… See the full description on the dataset page: https://huggingface.co/datasets/ColorfulAI/MoviePuzzle.

Explore the historical Whois records related to sweet-movie.net (Domain). Get insights into ownership history and changes over time.

Dataset Card for RLAIF-V-Bias-Dataset

🚀 Project Page: https://zhangzef.github.io/NaPO-Project-Page/ The RLAIF-V-Bias-Dataset is constructed based on the RLAIF-V-Dataset to mitigate the issue of modality bias in MLLMs using the LLaVA-v1.5-7b model.

RLAIF-V-Dataset provides high-quality feedback with a total number of 83,132 preference pairs, where the instructions are collected from a diverse range of datasets including MSCOCO, ShareGPT-4V, MovieNet, Google Landmark v2, VQA v2… See the full description on the dataset page: https://huggingface.co/datasets/Starrrrrry/RLAIF-V-Bias-Dataset.

Explore the historical Whois records related to diamond-movie.net (Domain). Get insights into ownership history and changes over time.

Explore the historical Whois records related to nadia-movie.net (Domain). Get insights into ownership history and changes over time.