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The capability to process multiple images is crucial for Large Vision-Language Models (LVLMs) to develop a more thorough and nuanced understanding of a scene.
The episodic buffer: a new component of working memory?
Alan Baddeley · 2000
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The iam-database: an english sentence database for offline handwriting recognition
U-V Marti and Horst Bunke · 2002
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The cognitive neuroscience of remote episodic, semantic and spatial memory
Morris Moscovitch, Lynn Nadel, Gordon Winocur, Asaf Gilboa, and R Shayna Rosenbaum · 2006
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Labeled faces in the wild: A database forstudying face recognition in unconstrained environments
Gary B Huang, Marwan Mattar, Tamara Berg, and Eric Learned-Miller · 2008
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Automated flower classification over a large number of classes
Maria-Elena Nilsback and Andrew Zisserman · 2008
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Collecting highly parallel data for paraphrase evaluation
David Chen and William B Dolan · 2011
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The caltech-ucsd birds-200-2011 dataset
Catherine Wah, Steve Branson, Peter Welinder, Pietro Perona, and Serge Belongie · 2011
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Indoor segmentation and support inference from rgbd images
Nathan Silberman, Derek Hoiem, Pushmeet Kohli, and Rob Fergus · 2012
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Vision meets robotics: The kitti dataset
Andreas Geiger, Philipp Lenz, and Raquel Urtasun · 2013
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Action recognition and detection by combining motion and appearance features
Limin Wang, Yu Qiao, Xiaoou Tang, et al · 2014
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Tiny imagenet visual recognition challenge
Ya Le and Xuan Yang · 2015
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Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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Large-scale classification of fine-art paintings: Learning the right metric on the right feature
Babak Saleh and Ahmed Elgammal · 2015
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Sun rgb-d: A rgb-d scene understanding benchmark suite
Shuran Song, Samuel P Lichtenberg, and Jianxiong Xiao · 2015
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Unsupervised learning of video representations using lstms
Nitish Srivastava, Elman Mansimov, and Ruslan Salakhudinov · 2015
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3d shapenets: A deep representation for volumetric shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
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Scalable person re-identification: A benchmark
Liang Zheng, Liyue Shen, Lu Tian, Shengjin Wang, Jingdong Wang, and Qi Tian · 2015
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Scenenet: An annotated model generator for indoor scene understanding
Ankur Handa, Viorica Pătrăucean, Simon Stent, and Roberto Cipolla · 2016
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A deep learning-based approach to progressive vehicle re-identification for urban surveillance
Xinchen Liu, Wu Liu, Tao Mei, and Huadong Ma · 2016
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Ntu rgb+d: A large scale dataset for 3d human activity analysis
Amir Shahroudy, Jun Liu, Tian-Tsong Ng, and Gang Wang · 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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Hpatches: A benchmark and evaluation of handcrafted and learned local descriptors
Vassileios Balntas, Karel Lenc, Andrea Vedaldi, and Krystian Mikolajczyk · 2017
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Matterport3d: Learning from rgb-d data in indoor environments
Angel X Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Jianxiong Xiao, Manolis Savva, Shuran Song, Andy Zeng, Yinda Zhang, and Matthias Nießner · 2017
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Scannet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
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A neural representation of sketch drawings
David Ha and Douglas Eck · 2017
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The kinetics human action video dataset
Will Kay, Joao Carreira, Karen Simonyan, Brian Zhang, Chloe Hillier, Sudheendra Vijayanarasimhan, Fabio Viola, Tim Green, Trevor Back, Paul Natsev, et al · 2017
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Learning to score olympic events
Paritosh Parmar and Brendan Tran Morris · 2017
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The 2017 davis challenge on video object segmentation
Jordi Pont-Tuset, Federico Perazzi, Sergi Caelles, Pablo Arbelaez, Alexander Sorkine-Hornung, and Luc Van Gool · 2017
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A corpus of natural language for visual reasoning
Alane Suhr, Mike Lewis, James Yeh, and Yoav Artzi · 2017
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Places: A 10 million image database for scene recognition
Bolei Zhou, Agata Lapedriza, Aditya Khosla, Aude Oliva, and Antonio Torralba · 2017
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A high-quality denoising dataset for smartphone cameras
Abdelrahman Abdelhamed, Stephen Lin, and Michael S Brown · 2018
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Learning to describe differences between pairs of similar images
Harsh Jhamtani and Taylor Berg-Kirkpatrick · 2018
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The sixth visual object tracking vot2018 challenge results
Matej Kristan, Jiri Matas, Ales Leonardis, Michael Felsberg, Roman Pflugfelder, Joni-Kristian Kamarainen, Martin Danelljan, Abdelrahman Eldesokey, Gabriel Fernandez, Alan Lukezic, et al · 2018
Cited alongside, same era.
Sqa3d: Situated question answering in 3d scenes
Xiaojian Ma, Silong Yong, Zilong Zheng, Qing Li, Yitao Liang, Song-Chun Zhu, and Siyuan Huang · 2022
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Videoabc: A real-world video dataset for abductive visual reasoning
Wenliang Zhao, Yongming Rao, Yansong Tang, Jie Zhou, and Jiwen Lu · 2022
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Claude, 2023
Anthropic · 2023
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Openflamingo: An open-source framework for training large autoregressive vision-language models
Anas Awadalla, Irena Gao, Josh Gardner, Jack Hessel, Yusuf Hanafy, Wanrong Zhu, Kalyani Marathe, Yonatan Bitton, Samir Gadre, Shiori Sagawa, et al · 2023
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Qwen-vl: A frontier large vision-language model with versatile abilities
Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou · 2023
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Zhengqi Li and Noah Snavely · 2018
Cited alongside, same era.
Totally looks like-how humans compare, compared to machines
Amir Rosenfeld, Markus D Solbach, and John K Tsotsos · 2018
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Measuring abstract reasoning in neural networks
Adam Santoro, Felix Hill, David Barrett, Ari Morcos, and Timothy Lillicrap · 2018
Cited alongside, same era.
Recipeqa: A challenge dataset for multimodal comprehension of cooking recipes
Semih Yagcioglu, Aykut Erdem, Erkut Erdem, and Nazli Ikizler-Cinbis · 2018
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From facial expression recognition to interpersonal relation prediction
Zhanpeng Zhang, Ping Luo, Chen Change Loy, and Xiaoou Tang · 2018
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Weakly-supervised video object grounding from text by loss weighting and object interaction
Luowei Zhou, Nathan Louis, and Jason J Corso · 2018
Cited alongside, same era.
Action-agnostic human pose forecasting
Hsu-kuang Chiu, Ehsan Adeli, Borui Wang, De-An Huang, and Juan Carlos Niebles · 2019
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Sharegpt4v: Improving large multi-modal models with better captions
Lin Chen, Jisong Li, Xiaoyi Dong, Pan Zhang, Conghui He, Jiaqi Wang, Feng Zhao, and Dahua Lin · 2023
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Opencompass: A universal evaluation platform for foundation models
OpenCompass Contributors · 2023
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Mevis: A large-scale benchmark for video segmentation with motion expressions
Henghui Ding, Chang Liu, Shuting He, Xudong Jiang, and Chen Change Loy · 2023
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Editing models with task arithmetic
Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, Suchin Gururangan, Ludwig Schmidt, Hannaneh Hajishirzi, and Ali Farhadi · 2023
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Mmbench: Is your multi-modal model an all-around player?
Yuan Liu, Haodong Duan, Yuanhan Zhang, Bo Li, Songyang Zhang, Wangbo Zhao, Yike Yuan, Jiaqi Wang, Conghui He, Ziwei Liu, et al · 2023
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Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts
Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chunyuan Li, Hannaneh Hajishirzi, Hao Cheng, Kai-Wei Chang, Michel Galley, and Jianfeng Gao · 2023
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Slidevqa: A dataset for document visual question answering on multiple images
Ryota Tanaka, Kyosuke Nishida, Kosuke Nishida, Taku Hasegawa, Itsumi Saito, and Kuniko Saito · 2023
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Gemini: a family of highly capable multimodal models
Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, et al · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
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Q-bench: A benchmark for general-purpose foundation models on low-level vision
Haoning Wu, Zicheng Zhang, Erli Zhang, Chaofeng Chen, Liang Liao, Annan Wang, Chunyi Li, Wenxiu Sun, Qiong Yan, Guangtao Zhai, et al · 2023
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Funqa: Towards surprising video comprehension
Binzhu Xie, Sicheng Zhang, Zitang Zhou, Bo Li, Yuanhan Zhang, Jack Hessel, Jingkang Yang, and Ziwei Liu · 2023
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Lvlm-ehub: A comprehensive evaluation benchmark for large vision-language models
Peng Xu, Wenqi Shao, Kaipeng Zhang, Peng Gao, Shuo Liu, Meng Lei, Fanqing Meng, Siyuan Huang, Yu Qiao, and Ping Luo · 2023
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Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi
Xiang Yue, Yuansheng Ni, Kai Zhang, Tianyu Zheng, Ruoqi Liu, Ge Zhang, Samuel Stevens, Dongfu Jiang, Weiming Ren, Yuxuan Sun, et al · 2023
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Xiaoyi Dong, Pan Zhang, Yuhang Zang, Yuhang Cao, Bin Wang, Linke Ouyang, Xilin Wei, Songyang Zhang, Haodong Duan, Maosong Cao, et al · 2024
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Chatglm: A family of large language models from glm-130b to glm-4 all tools
Team GLM, Aohan Zeng, Bin Xu, Bowen Wang, Chenhui Zhang, Da Yin, Diego Rojas, Guanyu Feng, Hanlin Zhao, Hanyu Lai, et al · 2024
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Minicpm: Unveiling the potential of small language models with scalable training strategies
Shengding Hu, Yuge Tu, Xu Han, Chaoqun He, Ganqu Cui, Xiang Long, Zhi Zheng, Yewei Fang, Yuxiang Huang, Weilin Zhao, et al · 2024
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Findingemo: An image dataset for emotion recognition in the wild
Laurent Mertens, Elahe’ Yargholi, Hans Op de Beeck, Jan Van den Stock, and Joost Vennekens · 2024
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Nuscenes-qa: A multi-modal visual question answering benchmark for autonomous driving scenario
Tianwen Qian, Jingjing Chen, Linhai Zhuo, Yang Jiao, and Yu-Gang Jiang · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean-baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, et al · 2024
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Milebench: Benchmarking mllms in long context
Dingjie Song, Shunian Chen, Guiming Hardy Chen, Fei Yu, Xiang Wan, and Benyou Wang · 2024
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Muirbench: A comprehensive benchmark for robust multi-image understanding
Fei Wang, Xingyu Fu, James Y Huang, Zekun Li, Qin Liu, Xiaogeng Liu, Mingyu Derek Ma, Nan Xu, Wenxuan Zhou, Kai Zhang, et al · 2024
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Kaining Ying, Fanqing Meng, Jin Wang, Zhiqian Li, Han Lin, Yue Yang, Hao Zhang, Wenbo Zhang, Yuqi Lin, Shuo Liu, et al · 2024
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Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi
Xiang Yue, Yuansheng Ni, Kai Zhang, Tianyu Zheng, Ruoqi Liu, Ge Zhang, Samuel Stevens, Dongfu Jiang, Weiming Ren, Yuxuan Sun, et al · 2024
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Multimodal c4: An open, billion-scale corpus of images interleaved with text
Wanrong Zhu, Jack Hessel, Anas Awadalla, Samir Yitzhak Gadre, Jesse Dodge, Alex Fang, Youngjae Yu, Ludwig Schmidt, William Yang Wang, and Yejin Choi · 2024
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