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The rapid development of diffusion models has greatly advanced AI-generated videos in terms of length and consistency recently, yet assessing AI-generated videos still remains challenging. Previous approaches have often focused on…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Jiaze Li , Haoran Xu , Shiding Zhu , Junwei He , Haozhao Wang

The recent advancements in text-to-3D generation mark a significant milestone in generative models, unlocking new possibilities for creating imaginative 3D assets across various real-world scenarios. While recent advancements in text-to-3D…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Yixun Liang , Xin Yang , Jiantao Lin , Haodong Li , Xiaogang Xu , Yingcong Chen

The rapid advancement in AI-generated video synthesis has led to a growth demand for standardized and effective evaluation metrics. Existing metrics lack a unified framework for systematically categorizing methodologies, limiting a holistic…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Xinhao Xiang , Xiao Liu , Zizhong Li , Zhuosheng Liu , Jiawei Zhang

Generative priors of large-scale text-to-image diffusion models enable a wide range of new generation and editing applications on diverse visual modalities. However, when adapting these priors to complex visual modalities, often represented…

Computer Vision and Pattern Recognition · Computer Science 2023-07-12 Subin Kim , Kyungmin Lee , June Suk Choi , Jongheon Jeong , Kihyuk Sohn , Jinwoo Shin

The rapid advancement of AI-generated video models has created a pressing need for robust and interpretable evaluation frameworks. Existing metrics are limited to producing numerical scores without explanatory comments, resulting in low…

Computer Vision and Pattern Recognition · Computer Science 2025-07-03 Xiao Liu , Jiawei Zhang

Long-term Video Question Answering (VideoQA) is a challenging vision-and-language bridging task focusing on semantic understanding of untrimmed long-term videos and diverse free-form questions, simultaneously emphasizing comprehensive…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Ting Yu , Kunhao Fu , Jian Zhang , Qingming Huang , Jun Yu

Evaluating text-to-image generative models remains a challenge, despite the remarkable progress being made in their overall performances. While existing metrics like CLIPScore work for coarse evaluations, they lack the sensitivity to…

Computer Vision and Pattern Recognition · Computer Science 2024-11-06 Georgia Gabriela Sampaio , Ruixiang Zhang , Shuangfei Zhai , Jiatao Gu , Josh Susskind , Navdeep Jaitly , Yizhe Zhang

Automated question generation is an important approach to enable personalisation of English comprehension assessment. Recently, transformer-based pretrained language models have demonstrated the ability to produce appropriate questions from…

Computation and Language · Computer Science 2022-09-27 Vatsal Raina , Mark Gales

Recent advances in text-to-video generation have achieved impressive performance on short clips, yet evaluating long-form generation under complex textual inputs remains a significant challenge. In response to this challenge, we present…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Xiangqing Zheng , Chengyue Wu , Kehai Chen , Min Zhang

The proliferation of online short video platforms has driven a surge in user demand for short video editing. However, manually selecting, cropping, and assembling raw footage into a coherent, high-quality video remains laborious and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Zhihui Yin , Ye Ma , Xipeng Cao , Bo Wang , Quan Chen , Peng Jiang

Sounding Video Generation (SVG) is an audio-video joint generation task challenged by high-dimensional signal spaces, distinct data formats, and different patterns of content information. To address these issues, we introduce a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Mingzhen Sun , Weining Wang , Yanyuan Qiao , Jiahui Sun , Zihan Qin , Longteng Guo , Xinxin Zhu , Jing Liu

The burgeoning field of Artificial Intelligence Generated Content (AIGC) is witnessing rapid advancements, particularly in video generation. This paper introduces AIGCBench, a pioneering comprehensive and scalable benchmark designed to…

Computer Vision and Pattern Recognition · Computer Science 2024-01-24 Fanda Fan , Chunjie Luo , Wanling Gao , Jianfeng Zhan

The development of AI-Generated Video (AIGV) technology has been remarkable in recent years, significantly transforming the paradigm of video content production. However, AIGVs still suffer from noticeable visual quality defects, such as…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Zelu Qi , Ping Shi , Chaoyang Zhang , Shuqi Wang , Fei Zhao , Da Pan , Zefeng Ying

Scaling multimodal large language models (MLLMs) to long videos is constrained by limited context windows. While retrieval-augmented generation (RAG) is a promising remedy by organizing query-relevant visual evidence into a compact context,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Honghao Fu , Miao Xu , Yiwei Wang , Dailing Zhang , Jun Liu , Yujun Cai

In recent years, artificial intelligence (AI)-driven video generation has gained significant attention. Consequently, there is a growing need for accurate video quality assessment (VQA) metrics to evaluate the perceptual quality of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Zhichao Zhang , Wei Sun , Xinyue Li , Jun Jia , Xiongkuo Min , Zicheng Zhang , Chunyi Li , Zijian Chen , Puyi Wang , Fengyu Sun , Shangling Jui , Guangtao Zhai

Multi-modal Large language models (MLLMs) show remarkable ability in video understanding. Nevertheless, understanding long videos remains challenging as the models can only process a finite number of frames in a single inference,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Yucheng Suo , Fan Ma , Linchao Zhu , Tianyi Wang , Fengyun Rao , Yi Yang

Unified multimodal models integrating visual understanding and generation face a fundamental challenge: visual generation incurs substantially higher computational costs than understanding, particularly for video. This imbalance motivates…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Luozheng Qin , Jia Gong , Qian Qiao , Tianjiao Li , Li Xu , Haoyu Pan , Chao Qu , Zhiyu Tan , Hao Li

A proper scene representation is central to the pursuit of spatial intelligence where agents can robustly reconstruct and efficiently understand 3D scenes. A scene representation is either metric, such as landmark maps in 3D reconstruction,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Juexiao Zhang , Gao Zhu , Sihang Li , Xinhao Liu , Haorui Song , Xinran Tang , Chen Feng

As a combination of visual and audio signals, video is inherently multi-modal. However, existing video generation methods are primarily intended for the synthesis of visual frames, whereas audio signals in realistic videos are disregarded.…

Computer Vision and Pattern Recognition · Computer Science 2023-06-16 Jiawei Liu , Weining Wang , Sihan Chen , Xinxin Zhu , Jing Liu

In real-world scenarios, providing user queries with visually enhanced responses can considerably benefit understanding and memory, underscoring the great value of interleaved image-text generation. Despite recent progress, like the visual…

Information Retrieval · Computer Science 2025-12-08 Rongyang Zhang , Yuqing Huang , Chengqiang Lu , Qimeng Wang , Yan Gao , Yi Wu , Yao Hu , Yin Xu , Wei Wang , Hao Wang , Enhong Chen