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Video Temporal Grounding (VTG) is a crucial capability for video understanding models and plays a vital role in downstream tasks such as video browsing and editing.
Meteor: An automatic metric for mt evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie · 2005
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Creating summaries from user videos
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Activitynet: A large-scale video benchmark for human activity understanding
Bernard Ghanem Fabian Caba Heilbron, Victor Escorcia and Juan Carlos Niebles · 2015
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Ramakrishna Vedantam, C Lawrence Zitnick, and Devi Parikh · 2015
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Towards automatic learning of procedures from web instructional videos
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Cater: A diagnostic dataset for compositional actions and temporal reasoning
Rohit Girdhar and Deva Ramanan · 2019
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Kexin Yi, Chuang Gan, Yunzhu Li, Pushmeet Kohli, Jiajun Wu, Antonio Torralba, and Joshua B Tenenbaum · 2019
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Soichiro Fujita, Tsutomu Hirao, Hidetaka Kamigaito, Manabu Okumura, and Masaaki Nagata · 2020
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Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei · 2020
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Causal discovery in physical systems from videos
Yunzhu Li, Antonio Torralba, Anima Anandkumar, Dieter Fox, and Animesh Garg · 2020
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Qvhighlights: Detecting moments and highlights in videos via natural language queries.(2021)
J Lei, TL Berg, and M Bansal · 2021
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Detecting moments and highlights in videos via natural language queries
Jie Lei, Tamara L Berg, and Mohit Bansal · 2021
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Queryd: A video dataset with high-quality text and audio narrations
Andreea-Maria Oncescu, Joao F Henriques, Yang Liu, Andrew Zisserman, and Samuel Albanie · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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End-to-end dense video captioning with parallel decoding
Teng Wang, Ruimao Zhang, Zhichao Lu, Feng Zheng, Ran Cheng, and Ping Luo · 2021
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Next-qa: Next phase of question-answering to explaining temporal actions
Junbin Xiao, Xindi Shang, Angela Yao, and Tat-Seng Chua · 2021
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Videoclip: Contrastive pre-training for zero-shot video-text understanding
Hu Xu, Gargi Ghosh, Po-Yao Huang, Dmytro Okhonko, Armen Aghajanyan, Florian Metze, Luke Zettlemoyer, and Christoph Feichtenhofer · 2021
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Merlot: Multimodal neural script knowledge models
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Complex video action reasoning via learnable markov logic network
Yang Jin, Linchao Zhu, and Yadong Mu · 2022
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Visual abductive reasoning
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Umt: Unified multi-modal transformers for joint video moment retrieval and highlight detection
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The surprising effectiveness of multimodal large language models for video moment retrieval
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Videollama 2: Advancing spatial-temporal modeling and audio understanding in video-llms
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Towards event-oriented long video understanding
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Videomae: Masked autoencoders are data-efficient learners for self-supervised video pre-training
Zhan Tong, Yibing Song, Jue Wang, and Limin Wang · 2022
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Internvideo: General video foundation models via generative and discriminative learning
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Videococa: Video-text modeling with zero-shot transfer from contrastive captioners
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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Text-to-audio generation using instruction-tuned llm and latent diffusion model
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Vtimellm: Empower llm to grasp video moments
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Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al · 2023
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Llava-onevision: Easy visual task transfer
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Visual instruction tuning
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Number it: Temporal grounding videos like flipping manga
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Minicpm-v: A gpt-4v level mllm on your phone
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Video instruction tuning with synthetic data
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Videoprism: A foundational visual encoder for video understanding
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A large cross-modal video retrieval dataset with reading comprehension
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