Papers Unsupervised Video Summarization
“Unsupervised Video Summarization” 태그가 달린 논문 32편 · 필터 해제
Semantic-Guided Unsupervised Video Summarization
Video summarization is a crucial technique for social understanding, enabling efficient browsing of massive multimedia content and extraction of key information from social platforms. Most existing unsupervised summariza…
Unsupervised Video SummarizationIntegrate the temporal scheme for unsupervised video summarization via attention mechanism
In this work, we present a novel unsupervised scheme named SegSum, designed for video summarization through the creation of video skims. Most contemporary methods involve training a summarizer to assign importance scores…
Unsupervised Video SummarizationVideo SummarizationVideo Summarization using Denoising Diffusion Probabilistic Model
Video summarization aims to eliminate visual redundancy while retaining key parts of video to construct concise and comprehensive synopses. Most existing methods use discriminative models to predict the importance scores…
DenoisingmodelUnsupervised Video SummarizationVideo SummarizationPersonalized Video Summarization by Multimodal Video Understanding
Video summarization techniques have been proven to improve the overall user experience when it comes to accessing and comprehending video content. If the user's preference is known, video summarization can identify signi…
Unsupervised Video SummarizationVideo SummarizationVideo UnderstandingUnsupervised Video Summarization via Reinforcement Learning and a Trained Evaluator
This paper presents a novel approach for unsupervised video summarization using reinforcement learning. It aims to address the existing limitations of current unsupervised methods, including unstable training of adversar…
reinforcement-learningReinforcement LearningUnsupervised Video SummarizationVideo SummarizationEnhancing Video Summarization with Context Awareness
Video summarization is a crucial research area that aims to efficiently browse and retrieve relevant information from the vast amount of video content available today. With the exponential growth of multimedia data, the …
BenchmarkingInformativenessUnsupervised Video SummarizationVideo SummarizationCluster-based Video Summarization with Temporal Context Awareness
In this paper, we present TAC-SUM, a novel and efficient training-free approach for video summarization that addresses the limitations of existing cluster-based models by incorporating temporal context. Our method partit…
ClusteringUnsupervised Video SummarizationVideo SummarizationUnsupervised Video Summarization via Iterative Training and Simplified GAN
This paper introduces a new, unsupervised method for automatic video summarization using ideas from generative adversarial networks but eliminating the discriminator, having a simple loss function, and separating trainin…
Model SelectionUnsupervised Video SummarizationVideo SummarizationAdopting Self-Supervised Learning into Unsupervised Video Summarization through Restorative Score
In this paper, we present a new process for creating video summaries in an unsupervised manner. Our approach involves training a transformer encoder model to reconstruct missing frames in a video in a self-supervised way…
Self-Supervised LearningUnsupervised Video SummarizationVideo SummarizationAdopting Self-Supervised Learning into Unsupervised Video Summarization through Restorative Score.
In this paper, we present a new process for creating video summaries in an unsupervised manner. Our approach involves training a transformer encoder model to reconstruct missing frames in a video in a self-supervised way…
Self-Supervised LearningUnsupervised Video SummarizationVideo SummarizationSelf-Attention Based Generative Adversarial Networks For Unsupervised Video Summarization
In this paper, we study the problem of producing a comprehensive video summary following an unsupervised approach that relies on adversarial learning. We build on a popular method where a Generative Adversarial Network (…
Generative Adversarial NetworkUnsupervised Video SummarizationVideo SummarizationMasked Autoencoder for Unsupervised Video Summarization
Summarizing a video requires a diverse understanding of the video, ranging from recognizing scenes to evaluating how much each frame is essential enough to be selected as a summary. Self-supervised learning (SSL) is ackn…
DecoderSelf-Supervised LearningUnsupervised Video SummarizationVideo SummarizationLearning to Summarize Videos by Contrasting Clips
Video summarization aims at choosing parts of a video that narrate a story as close as possible to the original one. Most of the existing video summarization approaches focus on hand-crafted labels. As the number of vide…
Contrastive LearningUnsupervised Video SummarizationVideo SummarizationContrastive Losses Are Natural Criteria for Unsupervised Video Summarization
Video summarization aims to select the most informative subset of frames in a video to facilitate efficient video browsing. Unsupervised methods usually rely on heuristic training objectives such as diversity and represe…
Diversityimage-classificationImage ClassificationRepresentation Learning+2Summarizing Videos using Concentrated Attention and Considering the Uniqueness and Diversity of the Video Frames
In this work, we describe a new method for unsupervised video summarization. To overcome limitations of existing unsupervised video summarization approaches, that relate to the unstable training of Generator-Discriminato…
BenchmarkingDiversityUnsupervised Video SummarizationVideo SummarizationERA: Entity Relationship Aware Video Summarization with Wasserstein GAN
Video summarization aims to simplify large scale video browsing by generating concise, short summaries that diver from but well represent the original video. Due to the scarcity of video annotations, recent progress for …
Unsupervised Video SummarizationVideo SummarizationSelf-Attention Recurrent Summarization Network with Reinforcement Learning for Video Summarization Task
With the exponential growth of video data, video summarization techniques are urgently needed for reducing people’s efforts in the videos' content exploration by generating succinct but informative summaries from origina…
reinforcement-learningReinforcement LearningSupervised Video SummarizationUnsupervised Video Summarization+1Unsupervised Video Summarization via Multi-source Features
Video summarization aims at generating a compact yet representative visual summary that conveys the essence of the original video. The advantage of unsupervised approaches is that they do not require human annotations to…
Unsupervised Video SummarizationVideo SummarizationUnsupervised Video Summarization with a Convolutional Attentive Adversarial Network
With the explosive growth of video data, video summarization, which attempts to seek the minimum subset of frames while still conveying the main story, has become one of the hottest topics. Nowadays, substantial achievem…
Generative Adversarial NetworkUnsupervised Video SummarizationVideo SummarizationAC-SUM-GAN: Connecting Actor-Critic and Generative Adversarial Networks for Unsupervised Video Summarization
This paper presents a new method for unsupervised video summarization. The proposed architecture embeds an Actor-Critic model into a Generative Adversarial Network and formulates the selection of important video fragment…
Generative Adversarial NetworkUnsupervised Video SummarizationVideo Summarization