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To solve video-and-language grounding tasks, the key is for the network to understand the connection between the two modalities. For a pair of video and language description, their semantic relation is reflected by their encodings'…

Computer Vision and Pattern Recognition · Computer Science 2023-02-28 Yubo Zhang , Feiyang Niu , Qing Ping , Govind Thattai

Video temporal grounding (VTG) aims to locate precise segments in videos based on language queries, which is a fundamental challenge in video understanding. While recent Multimodal Large Language Models (MLLMs) have shown promise in…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Lu Dong , Haiyu Zhang , Han Lin , Ziang Yan , Xiangyu Zeng , Hongjie Zhang , Yifei Huang , Yi Wang , Zhen-Hua Ling , Limin Wang , Yali Wang

Temporal video grounding (TVG) aims to localize a target segment in a video according to a given sentence query. Though respectable works have made decent achievements in this task, they severely rely on abundant video-query paired data,…

Computer Vision and Pattern Recognition · Computer Science 2022-01-17 Daizong Liu , Xiaoye Qu , Yinzhen Wang , Xing Di , Kai Zou , Yu Cheng , Zichuan Xu , Pan Zhou

Long Video Temporal Grounding (LVTG) aims at identifying specific moments within lengthy videos based on user-provided text queries for effective content retrieval. The approach taken by existing methods of dividing video into clips and…

Computer Vision and Pattern Recognition · Computer Science 2025-05-23 Zijia Lu , A S M Iftekhar , Gaurav Mittal , Tianjian Meng , Xiawei Wang , Cheng Zhao , Rohith Kukkala , Ehsan Elhamifar , Mei Chen

Temporal Video Grounding (TVG) aims to localize video segments corresponding to a given textual query, which often describes human actions. However, we observe that current methods, usually optimizing for high temporal…

Artificial Intelligence · Computer Science 2026-02-16 Zhaoyu Chen , Hongnan Lin , Yongwei Nie , Fei Ma , Xuemiao Xu , Fei Yu , Chengjiang Long

Spatio-temporal video grounding (STVG) aims to localize queried objects within dynamic video segments. Prevailing fully-trained approaches are notoriously data-hungry. However, gathering large-scale STVG data is exceptionally challenging:…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Zanyi Wang , Fan Li , Dengyang Jiang , Liuzhuozheng Li , Yunhua Zhong , Guang Dai , Mengmeng Wang

Visual Grounding (VG) aims to locate the most relevant region in an image, based on a flexible natural language query but not a pre-defined label, thus it can be a more useful technique than object detection in practice. Most…

Computer Vision and Pattern Recognition · Computer Science 2019-03-19 Chaorui Deng , Qi Wu , Guanghui Xu , Zhuliang Yu , Yanwu Xu , Kui Jia , Mingkui Tan

In this work, we tackle the problem of long-form video-language grounding (VLG). Given a long-form video and a natural language query, a model should temporally localize the precise moment that answers the query. Humans can easily solve VLG…

Computer Vision and Pattern Recognition · Computer Science 2024-08-07 Hyogun Lee , Soyeon Hong , Mujeen Sung , Jinwoo Choi

Video grounding is a fundamental problem in multimodal content understanding, aiming to localize specific natural language queries in an untrimmed video. However, current video grounding datasets merely focus on simple events and are either…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Chaolei Tan , Zihang Lin , Junfu Pu , Zhongang Qi , Wei-Yi Pei , Zhi Qu , Yexin Wang , Ying Shan , Wei-Shi Zheng , Jian-Fang Hu

Text-guided 3D visual grounding (T-3DVG), which aims to locate a specific object that semantically corresponds to a language query from a complicated 3D scene, has drawn increasing attention in the 3D research community over the past few…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Daizong Liu , Yang Liu , Wencan Huang , Wei Hu

Video temporal grounding (VTG) is a fine-grained video understanding problem that aims to ground relevant clips in untrimmed videos given natural language queries. Most existing VTG models are built upon frame-wise final-layer CLIP…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Ye Liu , Jixuan He , Wanhua Li , Junsik Kim , Donglai Wei , Hanspeter Pfister , Chang Wen Chen

This paper addresses the problem of text-to-video temporal grounding, which aims to identify the time interval in a video semantically relevant to a text query. We tackle this problem using a novel regression-based model that learns to…

Computer Vision and Pattern Recognition · Computer Science 2020-04-17 Jonghwan Mun , Minsu Cho , Bohyung Han

In vision-language models (VLMs), misalignment between textual descriptions and visual coordinates often induces hallucinations. This issue becomes particularly severe in dense prediction tasks such as spatial-temporal video grounding…

Computer Vision and Pattern Recognition · Computer Science 2026-02-13 Xiaowen Zhang , Zhi Gao , Licheng Jiao , Lingling Li , Qing Li

Temporal grounding aims to localize a video moment which is semantically aligned with a given natural language query. Existing methods typically apply a detection or regression pipeline on the fused representation with the research focus on…

Computer Vision and Pattern Recognition · Computer Science 2021-12-16 Zhenzhi Wang , Limin Wang , Tao Wu , Tianhao Li , Gangshan Wu

3D visual grounding aims to localize the unique target described by natural languages in 3D scenes. The significant gap between 3D and language modalities makes it a notable challenge to distinguish multiple similar objects through the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Feng Xiao , Hongbin Xu , Guocan Zhao , Wenxiong Kang

3D Visual Grounding (3DVG) and 3D Dense Captioning (3DDC) are two crucial tasks in various 3D applications, which require both shared and complementary information in localization and visual-language relationships. Therefore, existing…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Yongdong Luo , Haojia Lin , Xiawu Zheng , Yigeng Jiang , Fei Chao , Jie Hu , Guannan Jiang , Songan Zhang , Rongrong Ji

In a retrieval system, simultaneously achieving search accuracy and efficiency is inherently challenging. This challenge is particularly pronounced in partially relevant video retrieval (PRVR), where incorporating more diverse context…

Computer Vision and Pattern Recognition · Computer Science 2025-04-18 WonJun Moon , Cheol-Ho Cho , Woojin Jun , Minho Shim , Taeoh Kim , Inwoong Lee , Dongyoon Wee , Jae-Pil Heo

Constructing 4D language fields is crucial for embodied AI, augmented/virtual reality, and 4D scene understanding, as they provide enriched semantic representations of dynamic environments and enable open-vocabulary querying in complex…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Xianfeng Wu , Yajing Bai , Minghan Li , Xianzu Wu , Xueqi Zhao , Zhongyuan Lai , Wenyu Liu , Xinggang Wang

Visual Grounding (VG) is a crucial topic in the field of vision and language, which involves locating a specific region described by expressions within an image. To reduce the reliance on manually labeled data, unsupervised visual grounding…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Linhui Xiao , Xiaoshan Yang , Fang Peng , Ming Yan , Yaowei Wang , Changsheng Xu

Temporal Sentence Grounding (TSG), which aims to localize moments from videos based on the given natural language queries, has attracted widespread attention. Existing works are mainly designed for short videos, failing to handle TSG in…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Houlun Chen , Xin Wang , Hong Chen , Zihan Song , Jia Jia , Wenwu Zhu