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There has been a growing interest in solving Visual Question Answering (VQA) tasks that require the model to reason beyond the content present in the image. In this work, we focus on questions that require commonsense reasoning. In contrast…

Computer Vision and Pattern Recognition · Computer Science 2022-10-26 Sahithya Ravi , Aditya Chinchure , Leonid Sigal , Renjie Liao , Vered Shwartz

Grounding temporal video segments described in natural language queries effectively and efficiently is a crucial capability needed in vision-and-language fields. In this paper, we deal with the fast video temporal grounding (FVTG) task,…

Computer Vision and Pattern Recognition · Computer Science 2022-04-13 Ziyue Wu , Junyu Gao , Shucheng Huang , Changsheng Xu

Image captioning models generally lack the capability to take into account user interest, and usually default to global descriptions that try to balance readability, informativeness, and information overload. On the other hand, VQA models…

Computer Vision and Pattern Recognition · Computer Science 2021-11-12 Edwin G. Ng , Bo Pang , Piyush Sharma , Radu Soricut

Text-to-image multimodal tasks, generating/retrieving an image from a given text description, are extremely challenging tasks since raw text descriptions cover quite limited information in order to fully describe visually realistic images.…

Computer Vision and Pattern Recognition · Computer Science 2020-10-27 Soyeon Caren Han , Siqu Long , Siwen Luo , Kunze Wang , Josiah Poon

Visual grounding is a ubiquitous building block in many vision-language tasks and yet remains challenging due to large variations in visual and linguistic features of grounding entities, strong context effect and the resulting semantic…

Computer Vision and Pattern Recognition · Computer Science 2019-11-26 Yongfei Liu , Bo Wan , Xiaodan Zhu , Xuming He

The popularity of image sharing on social media and the engagement it creates between users reflects the important role that visual context plays in everyday conversations. We present a novel task, Image-Grounded Conversations (IGC), in…

Computation and Language · Computer Science 2017-04-21 Nasrin Mostafazadeh , Chris Brockett , Bill Dolan , Michel Galley , Jianfeng Gao , Georgios P. Spithourakis , Lucy Vanderwende

We motivate and propose a suite of simple but effective improvements for concept-to-text generation called SAPPHIRE: Set Augmentation and Post-hoc PHrase Infilling and REcombination. We demonstrate their effectiveness on generative…

Computation and Language · Computer Science 2021-12-03 Steven Y. Feng , Jessica Huynh , Chaitanya Narisetty , Eduard Hovy , Varun Gangal

Asking questions about visual environments is a crucial way for intelligent agents to understand rich multi-faceted scenes, raising the importance of Visual Question Generation (VQG) systems. Apart from being grounded to the image, existing…

Computer Vision and Pattern Recognition · Computer Science 2024-02-21 Li Mi , Syrielle Montariol , Javiera Castillo-Navarro , Xianjie Dai , Antoine Bosselut , Devis Tuia

Fine-grained knowledge is crucial for vision-language models to obtain a better understanding of the real world. While there has been work trying to acquire this kind of knowledge in the space of vision and language, it has mostly focused…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Melika Behjati , James Henderson

This paper studies constrained text generation, which is to generate sentences under certain pre-conditions. We focus on CommonGen, the task of generating text based on a set of concepts, as a representative task of constrained text…

Computation and Language · Computer Science 2021-03-15 Yixian Liu , Liwen Zhang , Wenjuan Han , Yue Zhang , Kewei Tu

Synthesizing realistic images from text descriptions on a dataset like Microsoft Common Objects in Context (MS COCO), where each image can contain several objects, is a challenging task. Prior work has used text captions to generate images.…

Computer Vision and Pattern Recognition · Computer Science 2018-02-23 Shikhar Sharma , Dendi Suhubdy , Vincent Michalski , Samira Ebrahimi Kahou , Yoshua Bengio

Recently, large-scale pre-trained language models have demonstrated impressive performance on several commonsense-reasoning benchmark datasets. However, building machines with commonsense to compose realistically plausible sentences remains…

Computation and Language · Computer Science 2020-12-01 Bill Yuchen Lin , Wangchunshu Zhou , Ming Shen , Pei Zhou , Chandra Bhagavatula , Yejin Choi , Xiang Ren

Recently, with the rapid advancements of generative models, the field of visual text generation has witnessed significant progress. However, it is still challenging to render high-quality text images in real-world scenarios, as three…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Yuanzhi Zhu , Jiawei Liu , Feiyu Gao , Wenyu Liu , Xinggang Wang , Peng Wang , Fei Huang , Cong Yao , Zhibo Yang

From the perspective of future developments in robotics, it is crucial to verify whether foundation models trained exclusively on offline data, such as images and language, can understand the robot motion. In particular, since Vision…

Robotics · Computer Science 2026-01-13 Kanata Suzuki , Shota Shimizu , Tetsuya Ogata

Video grounding aims to locate a moment of interest matching the given query sentence from an untrimmed video. Previous works ignore the {sparsity dilemma} in video annotations, which fails to provide the context information between…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Hongxiang Li , Meng Cao , Xuxin Cheng , Zhihong Zhu , Yaowei Li , Yuexian Zou

Video captioning is a challenging task since it requires generating sentences describing various diverse and complex videos. Existing video captioning models lack adequate visual representation due to the neglect of the existence of gaps…

Computer Vision and Pattern Recognition · Computer Science 2021-10-14 Mingkang Tang , Zhanyu Wang , Zhenhua Liu , Fengyun Rao , Dian Li , Xiu Li

With the rapid development of Artificial Intelligence Generated Content (AIGC), it has become a common practice to train models on synthetic data due to data-scarcity and privacy leakage problems. Owing to massive and diverse information…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Shiye Lei , Hao Chen , Sen Zhang , Bo Zhao , Dacheng Tao

Image Captioning is a fundamental task to join vision and language, concerning about cross-modal understanding and text generation. Recent years witness the emerging attention on image captioning. Most of existing works follow a traditional…

Computer Vision and Pattern Recognition · Computer Science 2022-04-15 Ziyang Luo , Yadong Xi , Rongsheng Zhang , Jing Ma

Recent advances in text-to-video (T2V) generation highlight the critical role of high-quality video-text pairs in training models capable of producing coherent and instruction-aligned videos. However, strategies for optimizing video…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Yang Du , Zhuoran Lin , Kaiqiang Song , Biao Wang , Zhicheng Zheng , Tiezheng Ge , Bo Zheng , Qin Jin

Visual dialogue is a challenging task since it needs to answer a series of coherent questions on the basis of understanding the visual environment. Previous studies focus on the implicit exploration of multimodal co-reference by implicitly…

Computation and Language · Computer Science 2021-09-20 Feilong Chen , Fandong Meng , Xiuyi Chen , Peng Li , Jie Zhou