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We propose StyleCap, a method to generate natural language descriptions of speaking styles appearing in speech. Although most of conventional techniques for para-/non-linguistic information recognition focus on the category classification…

Computation and Language · Computer Science 2023-12-29 Kazuki Yamauchi , Yusuke Ijima , Yuki Saito

The evaluation of machine-generated image captions is a complex and evolving challenge. With the advent of Multimodal Large Language Models (MLLMs), image captioning has become a core task, increasing the need for robust and reliable…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Sara Sarto , Marcella Cornia , Rita Cucchiara

Most current image captioning systems focus on describing general image content, and lack background knowledge to deeply understand the image, such as exact named entities or concrete events. In this work, we focus on the entity-aware news…

Computer Vision and Pattern Recognition · Computer Science 2021-08-05 Anwen Hu , Shizhe Chen , Qin Jin

Generating natural sentences from images is a fundamental learning task for visual-semantic understanding in multimedia. In this paper, we propose to apply dual attention on pyramid image feature maps to fully explore the visual-semantic…

Computer Vision and Pattern Recognition · Computer Science 2021-06-11 Litao Yu , Jian Zhang , Qiang Wu

This paper introduces QCaption, a novel video captioning and Q&A pipeline that enhances video analytics by fusing three models: key frame extraction, a Large Multimodal Model (LMM) for image-text analysis, and a Large Language Model (LLM)…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Jiale Wang , Gee Wah Ng , Lee Onn Mak , Randall Cher , Ng Ding Hei Ryan , Davis Wang

Recent multimodal large language models have shown promising ability in generating humorous captions for images, yet they still lack stable control over explicit cultural context, making it difficult to jointly maintain image relevance,…

Computation and Language · Computer Science 2026-04-21 Run Xu , Lu Li , Rongzhao Zhang , Jie Xu

The use of explicit object detectors as an intermediate step to image captioning - which used to constitute an essential stage in early work - is often bypassed in the currently dominant end-to-end approaches, where the language model is…

Computer Vision and Pattern Recognition · Computer Science 2018-05-02 Josiah Wang , Pranava Madhyastha , Lucia Specia

Recent advances in large language models (LLMs), such as ChatGPT, have led to highly sophisticated conversation agents. However, these models suffer from "hallucinations," where the model generates false or fabricated information.…

Computation and Language · Computer Science 2023-06-12 Philip Feldman , James R. Foulds , Shimei Pan

Semantic annotations are indispensable to train or evaluate perception models, yet very costly to acquire. This work introduces a fully automated 2D/3D labeling framework that, without any human intervention, can generate labels for RGB-D…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Silvan Weder , Hermann Blum , Francis Engelmann , Marc Pollefeys

Automatic music captioning, which generates natural language descriptions for given music tracks, holds significant potential for enhancing the understanding and organization of large volumes of musical data. Despite its importance,…

Sound · Computer Science 2023-08-01 SeungHeon Doh , Keunwoo Choi , Jongpil Lee , Juhan Nam

Real-time video commentary generation provides textual descriptions of ongoing events in videos. It supports accessibility and engagement in domains such as sports, esports, and livestreaming. Commentary generation involves two essential…

Computation and Language · Computer Science 2026-03-04 Anum Afzal , Yuki Saito , Hiroya Takamura , Katsuhito Sudoh , Shinnosuke Takamichi , Graham Neubig , Florian Matthes , Tatsuya Ishigaki

We introduce a novel framework for image captioning that can produce natural language explicitly grounded in entities that object detectors find in the image. Our approach reconciles classical slot filling approaches (that are generally…

Computer Vision and Pattern Recognition · Computer Science 2018-03-28 Jiasen Lu , Jianwei Yang , Dhruv Batra , Devi Parikh

While image captioning has progressed rapidly, existing works focus mainly on describing single images. In this paper, we introduce a new task, context-aware group captioning, which aims to describe a group of target images in the context…

Computer Vision and Pattern Recognition · Computer Science 2020-04-09 Zhuowan Li , Quan Tran , Long Mai , Zhe Lin , Alan Yuille

Automated visual story generation aims to produce stories with corresponding illustrations that exhibit coherence, progression, and adherence to characters' emotional development. This work proposes a story generation pipeline to co-create…

Artificial Intelligence · Computer Science 2023-01-10 Yuetian Chen , Ruohua Li , Bowen Shi , Peiru Liu , Mei Si

The advent of large Vision-Language Models (VLMs) has significantly advanced multimodal tasks, enabling more sophisticated and accurate reasoning across various applications, including image and video captioning, visual question answering,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Hang Hua , Qing Liu , Lingzhi Zhang , Jing Shi , Zhifei Zhang , Yilin Wang , Jianming Zhang , Jiebo Luo

Event-based image retrieval from free-form captions presents a significant challenge: models must understand not only visual features but also latent event semantics, context, and real-world knowledge. Conventional vision-language retrieval…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Dinh-Khoi Vo , Van-Loc Nguyen , Minh-Triet Tran , Trung-Nghia Le

Systems such as video chatbots and navigation robots often depend on streaming image captioning to interpret visual inputs. Existing approaches typically employ large multimodal language models (MLLMs) for this purpose, but their…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Junha Song , Yongsik Jo , So Yeon Min , Quanting Xie , Taehwan Kim , Yonatan Bisk , Jaegul Choo

Generating accurate descriptions for online fashion items is important not only for enhancing customers' shopping experiences, but also for the increase of online sales. Besides the need of correctly presenting the attributes of items, the…

Computer Vision and Pattern Recognition · Computer Science 2022-04-26 Xuewen Yang , Heming Zhang , Di Jin , Yingru Liu , Chi-Hao Wu , Jianchao Tan , Dongliang Xie , Jue Wang , Xin Wang

News image captioning requires model to generate an informative caption rich in entities, with the news image and the associated news article. Current MLLMs still bear limitations in handling entity information in news image captioning…

Computer Vision and Pattern Recognition · Computer Science 2024-09-23 Junzhe Zhang , Huixuan Zhang , Xunjian Yin , Xiaojun Wan

This paper introduces text2midi, an end-to-end model to generate MIDI files from textual descriptions. Leveraging the growing popularity of multimodal generative approaches, text2midi capitalizes on the extensive availability of textual…

Sound · Computer Science 2025-06-18 Keshav Bhandari , Abhinaba Roy , Kyra Wang , Geeta Puri , Simon Colton , Dorien Herremans