the frame extractor for Video Datasets with GPU Acceleration
-
Updated
Dec 24, 2020 - Python
the frame extractor for Video Datasets with GPU Acceleration
Trailers12k is a video movie trailer dataset composed of 12,000 titles associated to 10 genres. It distinguishes from other datasets by its collection procedure aiming to provide a high-quality publicly available dataset.
This annotation tool is build to clean and create video dataset.
UG2: a Video Benchmark for Assessing the Impact of Image Restoration and Enhancement on Automatic Visual Recognition
🧠️🖥️2️⃣️0️⃣️0️⃣️1️⃣️📽️📸️ The video:photography category for AI2001, containing photography video datasets
🧠️🖥️2️⃣️0️⃣️0️⃣️1️⃣️📽️
🧠️🖥️2️⃣️0️⃣️0️⃣️1️⃣️📽️🕹️ The video:gameplay category for AI2001, containing gameplay video datasets
🧠️🖥️2️⃣️0️⃣️0️⃣️1️⃣️📽️👁️ The video:animation:anime category for AI2001, containing Aime video datasets
🧠️🖥️2️⃣️0️⃣️0️⃣️1️⃣️📽️ The video category for AI2001, containing video datasets
🧠️🖥️2️⃣️0️⃣️0️⃣️1️⃣️📽️🌳️ The video:nature category for AI2001, containing nature video datasets
LIVE-YT-HFR Video Quality Assessment Database
Synthetically Generated Surveillance Perspective Human Action Recognition Dataset: 6901 Videos from 10 action classes, made by a 3D Simulation, all cropped spatio-temporally and filmed from a surveillance-camera like position.
Dataset repository of "MetaVD: A Meta Video Dataset for enhancing human action recognition datasets."
The repository contains the code for extracting image and mask from a video segmentation dataset by using the OpenCV library in the Python programming language.
Improving Transfer Learning with a Dual Image and Video Transformer for Multi-label Movie Trailer Genre Classification
Official This-Is-My Dataset published in CVPR 2023
[NeurIPS'22] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training
[AAAI 2023] AVCAffe: A Large Scale Audio-Visual Dataset of Cognitive Load and Affect for Remote Work
Add a description, image, and links to the video-dataset topic page so that developers can more easily learn about it.
To associate your repository with the video-dataset topic, visit your repo's landing page and select "manage topics."