TransNet V2: Shot Boundary Detection Neural Network

Automagically generate thumbnails, animated GIFs, and summaries from videos

AutoShot: A Short Video Dataset and State-of-the-Art Shot Boundary Detection - CVPR NAS 2023

ClipShots is the first large-scale dataset for shot boundary detection collected from Youtube and Weibo covering more than 20 categories, including sports, TV shows, animals, etc.

Large-scale, Fast and Accurate Shot Boundary Detection through Spatio-temporal Convolutional Neural Networks

Implementation of the paper 'Ridiculously Fast Shot Boundary Detection with Fully Convolutional Neural Networks' from scratch.

TransNet: A deep network for fast detection of common shot transitions

Open source software that detects shot boundaries in video.

Shot boundary detection (SBD) python program: Internship (Summer 2016) project

A simple GUI to show shot boundary detection based on TransNet V2.

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Video shot transition detection

Worked towards using the encoder-decoder network along with long short term memory (LSTM) network in order to develop the framework for solving the video matting problem.

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There's a good amount of literature on shot boundary detection, and there's a multitude of techniques that work successfully for hard-cuts, and more modern techniques like neural networks for fades/dissolves, wipes, etc. In this repository, I survey and implement/use tools to detect cuts with different kinds of content.

Detects shot boundaries from news with K-Means. Using Bhattacharya Coefficient for distance.

shot_boundary_detection

Shot_Boundary_Detection at Matlab

This is a package to do shot boundary detection on videos.

A shot is a continious sequence of frames filmed in one go. The regions of discrepency between two shots is called the shot boundary. Various discriminatory features like the frame variance, mean, L2-norm etc are taken (as a means of representing video frame data) and then various classifiers are used to compare their performances in detecting these shot boundaries.

shot boundary detection(video classification) by fully convolutional network

A simple scene boundary/shot transition detector with OpenCV.

Video shot detection is a computer vision technique used to automatically identify the boundaries between shots in a video sequence.

The project aims to segment scenes in movies using a mulitimodality framework that combines shot segmentation, object detection, and object-based shot matching. It utilizes Convolutional Neural Networks (CNN) and set theory to accurately detect scene boundaries, providing a semantic-based navigation system for intuitive interaction with movies

Histogram Difference based Shot Boundary detection, as used in Jung et al.'s paper on recaptured video detection, 2015.

The official source code for RSED: Zero-Shot Relation Triplet Extraction via Relation Selection and Entity Boundary Detection

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This project explores various similarity-learning loss formulations for solving tasks like fine-grained video/image retrieval or ranking, fine-grained video recognition.

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