Hybrid multi scale hard switch YOLOv4 network for cricket video summarization

Graph Hybrid Summarization

One solution to process and analysis of massive graphs is summarization. Generating a high quality summary is the main challenge of graph summarization. In the aims of generating a summary with a better quality for a given attributed graph, both structural and attribute similarities must be considered. There are two measures named density and entropy to evaluate the quality of structural and at...

Diversity-aware Multi-Video Summarization (Supplementary Material)

A Unified Multi-Faceted Video Summarization System

T his paper addresses automatic summarization and search in visual data comprising of videos, live streams and image collections in a unified manner. In particular, we propose a framework for multi-faceted summarization which extracts keyframes (image summaries), skims (video summaries) and entity summaries (summarization at the level of entities like objects, scenes, humans and faces in the vi...

Multi-Scale Video Frame-Synthesis Network with Transitive Consistency Loss

Traditional approaches to interpolate/extrapolate frames in a video sequence require accurate pixel correspondences between images, e.g., using optical flow. Their results stem on the accuracy of optical flow estimation, and could generate heavy artifacts when flow estimation failed. Recently methods using auto-encoder has shown impressive progress, however they are usually trained for specific...

A Multi-scale Multiple Instance Video Description Network

Generating natural language descriptions for in-thewild videos is a challenging task. Most state-of-the-art methods for solving this problem borrow existing deep convolutional neural network (CNN) architectures (Alexnet, Googlenet) to extract a visual representation of the input video. However, these deep CNN architectures are designed for single-label centered-positioned object classification....