1. 程式人生 > >深度學習之視訊語音+視訊摘要+視訊顯示檢測+視訊理解--附帶原始碼和作者主頁

深度學習之視訊語音+視訊摘要+視訊顯示檢測+視訊理解--附帶原始碼和作者主頁

視訊語音

Vid2speech: Speech Reconstruction from Silent Video

視訊摘要

Video summarization produces a short summary of a full-length video and ideally encapsulates its most informative parts, alleviates the problem of video browsing, editing and indexing.

Video Summarization with Long Short-term Memory

DeepVideo: Video Summarization using Temporal Sequence Modelling

Semantic Video Trailers

Video Summarization using Deep Semantic Features

CNN-Based Prediction of Frame-Level Shot Importance for Video Summarization

  • intro: International Conference on new Trends in Computer Sciences (ICTCS), Amman-Jordan, 2017

Video Summarization with Attention-Based Encoder-Decoder Networks

Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward

Viewpoint-aware Video Summarization

DTR-GAN: Dilated Temporal Relational Adversarial Network for Video Summarization

Learning Video Summarization Using Unpaired Data

Video Summarization Using Fully Convolutional Sequence Networks

Video Summarisation by Classification with Deep Reinforcement Learning

Query-Conditioned Three-Player Adversarial Network for Video Summarization

視訊突出顯示檢測

Unsupervised Extraction of Video Highlights Via Robust Recurrent Auto-encoders

  • intro: ICCV 2015
  • intro: rely on an assumption that highlights of an event category are more frequently captured in short videos than non-highlights

Highlight Detection with Pairwise Deep Ranking for First-Person Video Summarization

Using Deep Learning to Find Basketball Highlights

Real-Time Video Highlights for Yahoo Esports

A Deep Ranking Model for Spatio-Temporal Highlight Detection from a 360 Video

PHD-GIFs: Personalized Highlight Detection for Automatic GIF Creation

  • intro: Nanyang Technological University & Google Research, Zurich
  • keywords: personalized highlight detection (PHD)

視訊理解

Scale Up Video Understandingwith Deep Learning

Slicing Convolutional Neural Network for Crowd Video Understanding

Rethinking Spatiotemporal Feature Learning For Video Understanding

Hierarchical Video Understanding