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We introduce Tarsier2, a state-of-the-art large vision-language model (LVLM) designed for generating detailed and accurate video descriptions, while also exhibiting superior general video understanding capabilities.
Icdar 2003 robust reading competitions: entries, results, and future directions
Simon M Lucas, Alex Panaretos, Luis Sosa, Anthony Tang, Shirley Wong, Robert Young, Kazuki Ashida, Hiroki Nagai, Masayuki Okamoto, Hiroaki Yamamoto, et al · 2005
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Im2text: Describing images using 1 million captioned photographs
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Microsoft coco: Common objects in context
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Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models
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Visual storytelling
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Tgif: A new dataset and benchmark on animated gif description
Yuncheng Li, Yale Song, Liangliang Cao, Joel Tetreault, Larry Goldberg, Alejandro Jaimes, and Jiebo Luo · 2016
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Hollywood in homes: Crowdsourcing data collection for activity understanding
Gunnar A Sigurdsson, Gül Varol, Xiaolong Wang, Ali Farhadi, Ivan Laptev, and Abhinav Gupta · 2016
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Coco-text: Dataset and benchmark for text detection and recognition in natural images
Andreas Veit, Tomas Matera, Lukas Neumann, Jiri Matas, and Serge Belongie · 2016
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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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Localizing moments in video with natural language
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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Tall: Temporal activity localization via language query
Jiyang Gao, Chen Sun, Zhenheng Yang, and Ram Nevatia · 2017
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The” something something” video database for learning and evaluating visual common sense
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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The thumos challenge on action recognition for videos “in the wild”
Haroon Idrees, Amir R Zamir, Yu-Gang Jiang, Alex Gorban, Ivan Laptev, Rahul Sukthankar, and Mubarak Shah · 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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Visual genome: Connecting language and vision using crowdsourced dense image annotations
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A Shamma, et al · 2017
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Movie description
Anna Rohrbach, Atousa Torabi, Marcus Rohrbach, Niket Tandon, Christopher Pal, Hugo Larochelle, Aaron Courville, and Bernt Schiele · 2017
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Icdar2017 competition on reading chinese text in the wild (rctw-17)
Baoguang Shi, Cong Yao, Minghui Liao, Mingkun Yang, Pei Xu, Linyan Cui, Serge Belongie, Shijian Lu, and Xiang Bai · 2017
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Ava: A video dataset of spatio-temporally localized atomic visual actions
Chunhui Gu, Chen Sun, David A Ross, Carl Vondrick, Caroline Pantofaru, Yeqing Li, Sudheendra Vijayanarasimhan, George Toderici, Susanna Ricco, Rahul Sukthankar, et al · 2018
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Charades-ego: A large-scale dataset of paired third and first person videos
Gunnar A Sigurdsson, Abhinav Gupta, Cordelia Schmid, Ali Farhadi, and Karteek Alahari · 2018
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Visual to sound: Generating natural sound for videos in the wild
Yipin Zhou, Zhaowen Wang, Chen Fang, Trung Bui, and Tamara L Berg · 2018
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Abductive commonsense reasoning
Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, Keisuke Sakaguchi, Ari Holtzman, Hannah Rashkin, Doug Downey, Scott Wen-tau Yih, and Yejin Choi · 2019
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Egovqa-an egocentric video question answering benchmark dataset
Chenyou Fan · 2019
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin Ming-Wei Chang Kenton and Lee Kristina Toutanova · 2019
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The jester dataset: A large-scale video dataset of human gestures
Joanna Materzynska, Guillaume Berger, Ingo Bax, and Roland Memisevic · 2019
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Howto100m: Learning a text-video embedding by watching hundred million narrated video clips
Antoine Miech, Dimitri Zhukov, Jean-Baptiste Alayrac, Makarand Tapaswi, Ivan Laptev, and Josef Sivic · 2019
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Cord: a consolidated receipt dataset for post-ocr parsing
Seunghyun Park, Seung Shin, Bado Lee, Junyeop Lee, Jaeheung Surh, Minjoon Seo, and Hwalsuk Lee · 2019
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Icdar 2019 competition on large-scale street view text with partial labeling-rrc-lsvt
Yipeng Sun, Zihan Ni, Chee-Kheng Chng, Yuliang Liu, Canjie Luo, Chun Chet Ng, Junyu Han, Errui Ding, Jingtuo Liu, Dimosthenis Karatzas, et al · 2019
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Coin: A large-scale dataset for comprehensive instructional video analysis
Yansong Tang, Dajun Ding, Yongming Rao, Yu Zheng, Danyang Zhang, Lili Zhao, Jiwen Lu, and Jie Zhou · 2019
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Vatex: A large-scale, high-quality multilingual dataset for video-and-language research
Xin Wang, Jiawei Wu, Junkun Chen, Lei Li, Yuan-Fang Wang, and William Yang Wang · 2019
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Clevrer: Collision events for video representation and reasoning
Kexin Yi, Chuang Gan, Yunzhu Li, Pushmeet Kohli, Jiajun Wu, Antonio Torralba, and Joshua B Tenenbaum · 2019
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Icdar 2019 robust reading challenge on reading chinese text on signboard
Rui Zhang, Yongsheng Zhou, Qianyi Jiang, Qi Song, Nan Li, Kai Zhou, Lei Wang, Dong Wang, Minghui Liao, Mingkun Yang, et al · 2019
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Oops! predicting unintentional action in video
Dave Epstein, Boyuan Chen, and Carl Vondrick · 2020
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Hierarchical conditional relation networks for video question answering
Thao Minh Le, Vuong Le, Svetha Venkatesh, and Truyen Tran · 2020
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Rareact: A video dataset of unusual interactions
Antoine Miech, Jean-Baptiste Alayrac, Ivan Laptev, Josef Sivic, and Andrew Zisserman · 2020
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Frozen in time: A joint video and image encoder for end-to-end retrieval
Max Bain, Arsha Nagrani, Gül Varol, and Andrew Zisserman · 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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Spoken moments: Learning joint audio-visual representations from video descriptions
Mathew Monfort, SouYoung Jin, Alexander Liu, David Harwath, Rogerio Feris, James Glass, and Aude Oliva · 2021
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Multi-moments in time: Learning and interpreting models for multi-action video understanding
Mathew Monfort, Bowen Pan, Kandan Ramakrishnan, Alex Andonian, Barry A McNamara, Alex Lascelles, Quanfu Fan, Dan Gutfreund, Rogério Schmidt Feris, and Aude Oliva · 2021
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Ego4d: Around the world in 3,000 hours of egocentric video
Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, et al · 2022
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Egotaskqa: Understanding human tasks in egocentric videos
Baoxiong Jia, Ting Lei, Song-Chun Zhu, and Siyuan Huang · 2022
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Ocr-free document understanding transformer
Geewook Kim, Teakgyu Hong, Moonbin Yim, JeongYeon Nam, Jinyoung Park, Jinyeong Yim, Wonseok Hwang, Sangdoo Yun, Dongyoon Han, and Seunghyun Park · 2022
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Fineaction: A fine-grained video dataset for temporal action localization
Yi Liu, Limin Wang, Yali Wang, Xiao Ma, and Yu Qiao · 2022
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Towards end-to-end unified scene text detection and layout analysis
Shangbang Long, Siyang Qin, Dmitry Panteleev, Alessandro Bissacco, Yasuhisa Fujii, and Michalis Raptis · 2022
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Mmbench-video: A long-form multi-shot benchmark for holistic video understanding
Xinyu Fang, Kangrui Mao, Haodong Duan, Xiangyu Zhao, Yining Li, Dahua Lin, and Kai Chen · 2024
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Video-mme: The first-ever comprehensive evaluation benchmark of multi-modal llms in video analysis
Chaoyou Fu, Yuhan Dai, Yongdong Luo, Lei Li, Shuhuai Ren, Renrui Zhang, Zihan Wang, Chenyu Zhou, Yunhang Shen, Mengdan Zhang, et al · 2024
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Vtg-llm: Integrating timestamp knowledge into video llms for enhanced video temporal grounding
Yongxin Guo, Jingyu Liu, Mingda Li, Xiaoying Tang, Xi Chen, and Bo Zhao · 2024
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Storyteller: Improving long video description through global audio-visual character identification
Yichen He, Yuan Lin, Jianchao Wu, Hanchong Zhang, Yuchen Zhang, and Ruicheng Le · 2024
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Hongwei Xue, Tiankai Hang, Yanhong Zeng, Yuchong Sun, Bei Liu, Huan Yang, Jianlong Fu, and Baining Guo · 2022
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Videococa: Video-text modeling with zero-shot transfer from contrastive captioners
Shen Yan, Tao Zhu, Zirui Wang, Yuan Cao, Mi Zhang, Soham Ghosh, Yonghui Wu, and Jiahui Yu · 2022
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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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Gpt-4v (ision) system card
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An overview on the evaluated video retrieval tasks at trecvid 2022
George Awad, Keith Curtis, Asad Butt, Jonathan Fiscus, Afzal Godil, Yooyoung Lee, Andrew Delgado, Eliot Godard, Lukas Diduch, Jeffrey Liu, et al · 2023
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Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond
Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou · 2023
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Sharegpt4v: Improving large multi-modal models with better captions
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Lita: Language instructed temporal-localization assistant
De-An Huang, Shijia Liao, Subhashree Radhakrishnan, Hongxu Yin, Pavlo Molchanov, Zhiding Yu, and Jan Kautz · 2024
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Aaron Hurst, Adam Lerer, Adam P Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, Alan Hayes, Alec Radford, et al · 2024
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Llava-next: What else influences visual instruction tuning beyond data, 2024
Bo Li, Hao Zhang, Kaichen Zhang, Dong Guo, Yuanhan Zhang, Renrui Zhang, Feng Li, Ziwei Liu, and Chunyuan Li · 2024
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Llava-onevision: Easy visual task transfer
Bo Li, Yuanhan Zhang, Dong Guo, Renrui Zhang, Feng Li, Hao Zhang, Kaichen Zhang, Peiyuan Zhang, Yanwei Li, Ziwei Liu, et al · 2024
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Aria: An open multimodal native mixture-of-experts model
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Mvbench: A comprehensive multi-modal video understanding benchmark
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Vila: On pre-training for visual language models
Ji Lin, Hongxu Yin, Wei Ping, Pavlo Molchanov, Mohammad Shoeybi, and Song Han · 2024
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Kangaroo: A powerful video-language model supporting long-context video input
Jiajun Liu, Yibing Wang, Hanghang Ma, Xiaoping Wu, Xiaoqi Ma, Xiaoming Wei, Jianbin Jiao, Enhua Wu, and Jie Hu · 2024
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Robomamba: Multimodal state space model for efficient robot reasoning and manipulation
Jiaming Liu, Mengzhen Liu, Zhenyu Wang, Lily Lee, Kaichen Zhou, Pengju An, Senqiao Yang, Renrui Zhang, Yandong Guo, and Shanghang Zhang · 2024
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E.t. bench: Towards open-ended event-level video-language understanding
Ye Liu, Zongyang Ma, Zhongang Qi, Yang Wu, Chang Wen Chen, and Ying Shan · 2024
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Tempcompass: Do video llms really understand videos?
Yuanxin Liu, Shicheng Li, Yi Liu, Yuxiang Wang, Shuhuai Ren, Lei Li, Sishuo Chen, Xu Sun, and Lu Hou · 2024
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Nvila: Efficient frontier visual language models, 2024
Zhijian Liu, Ligeng Zhu, Baifeng Shi, Zhuoyang Zhang, Yuming Lou, Shang Yang, Haocheng Xi, Shiyi Cao, Yuxian Gu, Dacheng Li, Xiuyu Li, Yunhao Fang, Yukang Chen, Cheng-Yu Hsieh, De-An Huang, An-Chieh Cheng, Vishwesh Nath, Jinyi Hu, Sifei Liu, Ranjay Krishna, Daguang Xu, Xiaolong Wang, Pavlo Molchanov, Jan Kautz, Hongxu Yin, Song Han, and Yao Lu · 2024
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Oryx mllm: On-demand spatial-temporal understanding at arbitrary resolution
Zuyan Liu, Yuhao Dong, Ziwei Liu, Winston Hu, Jiwen Lu, and Yongming Rao · 2024
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Openeqa: Embodied question answering in the era of foundation models
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Perception test: A diagnostic benchmark for multimodal video models
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Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn · 2024
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Tomato: Assessing visual temporal reasoning capabilities in multimodal foundation models
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Enhancing multimodal llm for detailed and accurate video captioning using multi-round preference optimization, 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context, 2024
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Elysium: Exploring object-level perception in videos via mllm
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Tarsier: Recipes for training and evaluating large video description models, 2024
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Slowfast-llava: A strong training-free baseline for video large language models
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Video instruction tuning with synthetic data
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Mlvu: A comprehensive benchmark for multi-task long video understanding
Junjie Zhou, Yan Shu, Bo Zhao, Boya Wu, Shitao Xiao, Xi Yang, Yongping Xiong, Bo Zhang, Tiejun Huang, and Zheng Liu · 2024
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Apollo: An exploration of video understanding in large multimodal models, 2024
Orr Zohar, Xiaohan Wang, Yann Dubois, Nikhil Mehta, Tong Xiao, Philippe Hansen-Estruch, Licheng Yu, Xiaofang Wang, Felix Juefei-Xu, Ning Zhang, Serena Yeung-Levy, and Xide Xia · 2024
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Multi-label cluster discrimination for visual representation learning
Xiang An, Kaicheng Yang, Xiangzi Dai, Ziyong Feng, and Jiankang Deng · 2025
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Llama-vid: An image is worth 2 tokens in large language models
Yanwei Li, Chengyao Wang, and Jiaya Jia · 2025
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