Procedure-Aware Pretraining for Instructional Video Understanding

Author:

Zhou Honglu1,Martín-Martín Roberto1,Kapadia Mubbasir2,Savarese Silvio1,Niebles Juan Carlos1

Affiliation:

1. Salesforce Research

2. Rutgers University

Funder

NSF

Publisher

IEEE

Reference88 articles.

1. Graph2vid: Flow graph to video grounding for weakly-supervised multi-step localization;dvornik;ArXiv Preprint,2022

2. Mpnet: Masked and permuted pre-training for language understanding;song;Advances in neural information processing systems,2020

3. Action Modifiers: Learning From Adverbs in Instructional Videos

4. Learning to Segment Actions from Visual and Language Instructions via Differentiable Weak Sequence Alignment

5. Unsupervised Procedure Learning via Joint Dynamic Summarization

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Every Problem, Every Step, All in Focus: Learning to Solve Vision-Language Problems With Integrated Attention;IEEE Transactions on Pattern Analysis and Machine Intelligence;2024-07

2. Weakly-Supervised Action Learning in Procedural Task Videos via Process Knowledge Decomposition;IEEE Transactions on Circuits and Systems for Video Technology;2024-07

3. Towards Flow Graph Prediction of Open-Domain Procedural Texts;Journal of Natural Language Processing;2024

4. Learning to Ground Instructional Articles in Videos through Narrations;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

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