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Current large multimodal models (LMMs) face significant challenges in processing and comprehending long-duration or high-resolution videos, which is mainly due to the lack of high-quality datasets.
Im2text: Describing images using 1 million captioned photographs
Vicente Ordonez, Girish Kulkarni, and Tamara Berg · 2011
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Ucf101: A dataset of 101 human actions classes from videos in the wild
K Soomro · 2012
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Adam: A method for stochastic optimization
Diederik P Kingma · 2014
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Msr-vtt: A large video description dataset for bridging video and language
Jun Xu, Tao Mei, Ting Yao, and Yong Rui · 2016
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Lisa Anne Hendricks, Oliver Wang, Eli Shechtman, Josef Sivic, Trevor Darrell, and Bryan Russell · 2017
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Quo vadis, action recognition? a new model and the kinetics dataset
Joao Carreira and Andrew Zisserman · 2017
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Raghav Goyal, Samira Ebrahimi Kahou, Vincent Michalski, Joanna Materzynska, Susanne Westphal, Heuna Kim, Valentin Haenel, Ingo Fruend, Peter Yianilos, Moritz Mueller-Freitag, et al · 2017
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Tgif-qa: Toward spatio-temporal reasoning in visual question answering
Yunseok Jang, Yale Song, Youngjae Yu, Youngjin Kim, and Gunhee Kim · 2017
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Dense-captioning events in videos
Ranjay Krishna, Kenji Hata, Frederic Ren, Li Fei-Fei, and Juan Carlos Niebles · 2017
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Video question answering via gradually refined attention over appearance and motion
Dejing Xu, Zhou Zhao, Jun Xiao, Fei Wu, Hanwang Zhang, Xiangnan He, and Yueting Zhuang · 2017
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mixup: Beyond empirical risk minimization
Hongyi Zhang · 2017
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Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning
Piyush Sharma, Nan Ding, Sebastian Goodman, and Radu Soricut · 2018
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Towards automatic learning of procedures from web instructional videos
Luowei Zhou, Chenliang Xu, and Jason Corso · 2018
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Activitynet-qa: A dataset for understanding complex web videos via question answering
Zhou Yu, Dejing Xu, Jun Yu, Ting Yu, Zhou Zhao, Yueting Zhuang, and Dacheng Tao · 2019
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Cutmix: Regularization strategy to train strong classifiers with localizable features
Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, and Youngjoon Yoo · 2019
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Zero: Memory optimizations toward training trillion parameter models
Samyam Rajbhandari, Jeff Rasley, Olatunji Ruwase, and Yuxiong He · 2020
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Sangdoo Yun, Seong Joon Oh, Byeongho Heo, Dongyoon Han, and Jinhyung Kim · 2020
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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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Laion-5b: An open large-scale dataset for training next generation image-text models
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Video-mme: The first-ever comprehensive evaluation benchmark of multi-modal llms in video analysis
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Miradata: A large-scale video dataset with long durations and structured captions
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Llmtest_needleinahaystack
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Valley: Video assistant with large language model enhanced ability
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Video-chatgpt: Towards detailed video understanding via large vision and language models
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Gemini: a family of highly capable multimodal models
Gemini Team, Rohan Anil, Sebastian Borgeaud, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, Katie Millican, et al · 2023
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Internvid: A large-scale video-text dataset for multimodal understanding and generation
Yi Wang, Yinan He, Yizhuo Li, Kunchang Li, Jiashuo Yu, Xin Ma, Xinhao Li, Guo Chen, Xinyuan Chen, Yaohui Wang, et al · 2023
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Video-llama: An instruction-tuned audio-visual language model for video understanding
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Hugo Laurençon, Léo Tronchon, Matthieu Cord, and Victor Sanh · 2024
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Openvid-1m: A large-scale high-quality dataset for text-to-video generation
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Moviechat: From dense token to sparse memory for long video understanding
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