Cover Image

A Reinforcement Learning-Based Automatic Video Editing Method Using Pre-trained Vision-Language Model

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hu, Panwen, Xiao, Nan, Li, Feifei, Chen, Yongquan, Huang, Rui
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A multi-purpose automatic editing system based on lecture semantics for remote education
by: Hu, Panwen, et al.
Published: (2024)

BridgeIV: Bridging Customized Image and Video Generation through Test-Time Autoregressive Identity Propagation
by: Hu, Panwen, et al.
Published: (2025)

Towards Balanced RGB-TSDF Fusion for Consistent Semantic Scene Completion by 3D RGB Feature Completion and a Classwise Entropy Loss Function
by: Ding, Laiyan, et al.
Published: (2024)

UniVid: Unifying Vision Tasks with Pre-trained Video Generation Models
by: Chen, Lan, et al.
Published: (2025)

Low-hallucination Synthetic Captions for Large-Scale Vision-Language Model Pre-training
by: Zhang, Xinsong, et al.
Published: (2025)

MAA: Meticulous Adversarial Attack against Vision-Language Pre-trained Models
by: Zhang, Peng-Fei, et al.
Published: (2025)

Scaling Pre-training to One Hundred Billion Data for Vision Language Models
by: Wang, Xiao, et al.
Published: (2025)

Sparse Reasoning is Enough: Biological-Inspired Framework for Video Anomaly Detection with Large Pre-trained Models
by: Huang, He, et al.
Published: (2025)

Semantics-enhanced Cross-modal Masked Image Modeling for Vision-Language Pre-training
by: Liu, Haowei, et al.
Published: (2024)

Are Large Pre-trained Vision Language Models Effective Construction Safety Inspectors?
by: Chen, Xuezheng, et al.
Published: (2025)

Omniview-Tuning: Boosting Viewpoint Invariance of Vision-Language Pre-training Models
by: Ruan, Shouwei, et al.
Published: (2024)

Understanding the Multi-modal Prompts of the Pre-trained Vision-Language Model
by: Ma, Shuailei, et al.
Published: (2023)

Reinforcing Pre-trained Models Using Counterfactual Images
by: Li, Xiang, et al.
Published: (2024)

MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models
by: Hua, Hang, et al.
Published: (2024)

FashionFAE: Fine-grained Attributes Enhanced Fashion Vision-Language Pre-training
by: Huang, Jiale, et al.
Published: (2024)

UniQA: Unified Vision-Language Pre-training for Image Quality and Aesthetic Assessment
by: Zhou, Hantao, et al.
Published: (2024)

AutoEval-Video: An Automatic Benchmark for Assessing Large Vision Language Models in Open-Ended Video Question Answering
by: Chen, Xiuyuan, et al.
Published: (2023)

3D Scene Graph Guided Vision-Language Pre-training
by: Liu, Hao, et al.
Published: (2024)

Continual Forgetting for Pre-trained Vision Models
by: Zhao, Hongbo, et al.
Published: (2024)

Can LLM-Generated Text Empower Surgical Vision-Language Pre-training?
by: Che, Chengan, et al.
Published: (2026)

Contrastive Language Video Time Pre-training
by: Liu, Hengyue, et al.
Published: (2024)

A Two-Stage Globally-Diverse Adversarial Attack for Vision-Language Pre-training Models
by: Chen, Wutao, et al.
Published: (2026)

Efficient and Effective Universal Adversarial Attack against Vision-Language Pre-training Models
by: Yang, Fan, et al.
Published: (2024)

Learning to Rank Pre-trained Vision-Language Models for Downstream Tasks
by: Ding, Yuhe, et al.
Published: (2024)

Sample-agnostic Adversarial Perturbation for Vision-Language Pre-training Models
by: Zheng, Haonan, et al.
Published: (2024)

CLIPose: Category-Level Object Pose Estimation with Pre-trained Vision-Language Knowledge
by: Lin, Xiao, et al.
Published: (2024)

DreamVideo: High-Fidelity Image-to-Video Generation with Image Retention and Text Guidance
by: Wang, Cong, et al.
Published: (2023)

Efficient Vision-Language Pre-training by Cluster Masking
by: Wei, Zihao, et al.
Published: (2024)

Enhancing Vision-Language Pre-training with Rich Supervisions
by: Gao, Yuan, et al.
Published: (2024)

AttentionDrag: Exploiting Latent Correlation Knowledge in Pre-trained Diffusion Models for Image Editing
by: Yang, Biao, et al.
Published: (2025)

VLP: A Survey on Vision-Language Pre-training
by: Chen, Feilong, et al.
Published: (2022)

Do Pre-trained Vision-Language Models Encode Object States?
by: Newman, Kaleb, et al.
Published: (2024)

Retaining and Enhancing Pre-trained Knowledge in Vision-Language Models with Prompt Ensembling
by: Kim, Donggeun, et al.
Published: (2024)

FILP-3D: Enhancing 3D Few-shot Class-incremental Learning with Pre-trained Vision-Language Models
by: Xu, Wan, et al.
Published: (2023)

Mind the Interference: Retaining Pre-trained Knowledge in Parameter Efficient Continual Learning of Vision-Language Models
by: Tang, Longxiang, et al.
Published: (2024)

Anatomical Structure-Guided Medical Vision-Language Pre-training
by: Li, Qingqiu, et al.
Published: (2024)

Winner Team Mia at TextVQA Challenge 2021: Vision-and-Language Representation Learning with Pre-trained Sequence-to-Sequence Model
by: Qiao, Yixuan, et al.
Published: (2021)

Multilingual Vision-Language Pre-training for the Remote Sensing Domain
by: Silva, João Daniel, et al.
Published: (2024)

Unsupervised Domain Adaption Harnessing Vision-Language Pre-training
by: Zhou, Wenlve, et al.
Published: (2024)

LaVieID: Local Autoregressive Diffusion Transformers for Identity-Preserving Video Creation
by: Song, Wenhui, et al.
Published: (2025)