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Human video generation is a dynamic and rapidly evolving task that aims to synthesize 2D human body video sequences with generative models given control conditions such as text, audio, and pose. With the potential for wide-ranging…

Computer Vision and Pattern Recognition · Computer Science 2024-07-12 Wentao Lei , Jinting Wang , Fengji Ma , Guanjie Huang , Li Liu

Learning hidden topics from data streams has become absolutely necessary but posed challenging problems such as concept drift as well as short and noisy data. Using prior knowledge to enrich a topic model is one of potential solutions to…

Machine Learning · Computer Science 2021-12-28 Ngo Van Linh , Tran Xuan Bach , Khoat Than

The best summary of a long video differs among different people due to its highly subjective nature. Even for the same person, the best summary may change with time or mood. In this paper, we introduce the task of generating customized…

Computer Vision and Pattern Recognition · Computer Science 2018-03-05 Jinsoo Choi , Tae-Hyun Oh , In So Kweon

Generative Pre-trained Transformer (GPT) is a state-of-the-art machine learning model capable of generating human-like text through natural language processing (NLP). GPT is trained on massive amounts of text data and uses deep learning…

Spatio-temporal consistency is a critical research topic in video generation. A qualified generated video segment must ensure plot plausibility and coherence while maintaining visual consistency of objects and scenes across varying…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Runze Zhang , Guoguang Du , Xiaochuan Li , Qi Jia , Liang Jin , Lu Liu , Jingjing Wang , Cong Xu , Zhenhua Guo , Yaqian Zhao , Xiaoli Gong , Rengang Li , Baoyu Fan

Videos, images, and sentences are mediums that can express the same semantics. One can imagine a picture by reading a sentence or can describe a scene with some words. However, even small changes in a sentence can cause a significant…

Computer Vision and Pattern Recognition · Computer Science 2019-01-01 Amir Mazaheri , Mubarak Shah

In recent years, interest in synthetic data has grown, particularly in the context of pre-training the image modality to support a range of computer vision tasks, including object classification, medical imaging etc. Previous work has…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Davyd Svyezhentsev , George Retsinas , Petros Maragos

Generating video stories from text prompts is a complex task. In addition to having high visual quality, videos need to realistically adhere to a sequence of text prompts whilst being consistent throughout the frames. Creating a benchmark…

We present an approach that exploits hierarchical Recurrent Neural Networks (RNNs) to tackle the video captioning problem, i.e., generating one or multiple sentences to describe a realistic video. Our hierarchical framework contains a…

Computer Vision and Pattern Recognition · Computer Science 2016-04-07 Haonan Yu , Jiang Wang , Zhiheng Huang , Yi Yang , Wei Xu

Automatically generating a natural language sentence to describe the content of an input video is a very challenging problem. It is an essential multimodal task in which auditory and visual contents are equally important. Although audio…

Computer Vision and Pattern Recognition · Computer Science 2018-12-10 Yapeng Tian , Chenxiao Guan , Justin Goodman , Marc Moore , Chenliang Xu

Generating customized content in videos has received increasing attention recently. However, existing works primarily focus on customized text-to-video generation for single subject, suffering from subject-missing and attribute-binding…

Computer Vision and Pattern Recognition · Computer Science 2024-05-22 Hong Chen , Xin Wang , Yipeng Zhang , Yuwei Zhou , Zeyang Zhang , Siao Tang , Wenwu Zhu

Video generation has many unique challenges beyond those of image generation. The temporal dimension introduces extensive possible variations across frames, over which consistency and continuity may be violated. In this study, we move…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Weixi Feng , Jiachen Li , Michael Saxon , Tsu-jui Fu , Wenhu Chen , William Yang Wang

While conventional methods for sequential learning focus on interaction between consecutive inputs, we suggest a new method which captures composite semantic flows with variable-length dependencies. In addition, the semantic structures…

Machine Learning · Computer Science 2019-01-29 Kyoung-Woon On , Eun-Sol Kim , Yu-Jung Heo , Byoung-Tak Zhang

We propose a novel domain-specific generative pre-training (DS-GPT) method for text generation and apply it to the product titleand review summarization problems on E-commerce mobile display.First, we adopt a decoder-only transformer…

Computation and Language · Computer Science 2021-12-17 Xueying Zhang , Yunjiang Jiang , Yue Shang , Zhaomeng Cheng , Chi Zhang , Xiaochuan Fan , Yun Xiao , Bo Long

We introduce the novel problem of automatically generating animated GIFs from video. GIFs are short looping video with no sound, and a perfect combination between image and video that really capture our attention. GIFs tell a story, express…

Computer Vision and Pattern Recognition · Computer Science 2016-05-17 Michael Gygli , Yale Song , Liangliang Cao

This paper presents a novel retrieval pipeline for video collections, which aims to retrieve the most significant parts of an edited video for a given query, and represent them with thumbnails which are at the same time semantically…

Computer Vision and Pattern Recognition · Computer Science 2016-04-12 Lorenzo Baraldi , Costantino Grana , Rita Cucchiara

Cognitive science has shown that humans perceive videos in terms of events separated by the state changes of dominant subjects. State changes trigger new events and are one of the most useful among the large amount of redundant information…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Yuxuan Wang , Difei Gao , Licheng Yu , Stan Weixian Lei , Matt Feiszli , Mike Zheng Shou

Video description is one of the most challenging problems in vision and language understanding due to the large variability both on the video and language side. Models, hence, typically shortcut the difficulty in recognition and generate…

Computer Vision and Pattern Recognition · Computer Science 2019-05-07 Luowei Zhou , Yannis Kalantidis , Xinlei Chen , Jason J. Corso , Marcus Rohrbach

If the video has long been mentioned as a widespread visualization form, the animation sequence in the video is mentioned as storytelling for people. Producing an animation requires intensive human labor from skilled professional artists to…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Thi-Ngoc-Hanh Le , Sheng-Yi Yao , Chun-Te Wu , Tong-Yee Lee

Real-world videos often have complex dynamics; and methods for generating open-domain video descriptions should be sensitive to temporal structure and allow both input (sequence of frames) and output (sequence of words) of variable length.…

Computer Vision and Pattern Recognition · Computer Science 2015-10-20 Subhashini Venugopalan , Marcus Rohrbach , Jeff Donahue , Raymond Mooney , Trevor Darrell , Kate Saenko