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The narrative quality of a video fundamentally determines its perceptual value. Although existing video generation methods can produce visually appealing content, they predominantly rely on sparse conditioning signals such as text prompts…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Zhida Zhang , Jie Ma , Zhan Peng , Haoxue Wu , Yang Han , Jun Liang , Jie Cao , Jing Li

A key challenge in manipulation is learning a policy that can robustly generalize to diverse visual environments. A promising mechanism for learning robust policies is to leverage video generative models, which are pretrained on large-scale…

Recent progress in generative video models, such as Veo-3, has shown surprising zero-shot reasoning abilities, creating a growing need for systematic and reliable evaluation. We introduce V-ReasonBench, a benchmark designed to assess video…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Yang Luo , Xuanlei Zhao , Baijiong Lin , Lingting Zhu , Liyao Tang , Yuqi Liu , Ying-Cong Chen , Shengju Qian , Xin Wang , Yang You

Talking head generation creates lifelike avatars from static portraits for virtual communication and content creation. However, current models do not yet convey the feeling of truly interactive communication, often generating one-way…

Machine Learning · Computer Science 2026-01-05 Taekyung Ki , Sangwon Jang , Jaehyeong Jo , Jaehong Yoon , Sung Ju Hwang

Texture map production is an important part of 3D modeling and determines the rendering quality. Recently, diffusion-based methods have opened a new way for texture generation. However, restricted control flexibility and limited prompt…

Graphics · Computer Science 2025-06-04 Dongyu Yan , Leyi Wu , Jiantao Lin , Luozhou Wang , Tianshuo Xu , Zhifei Chen , Zhen Yang , Lie Xu , Shunsi Zhang , Yingcong Chen

Composition is a cornerstone of visual aesthetics, influencing the appeal of an image. While its principles operate independently of specific content, in practice, composition is often coupled with semantics. As a result, existing methods…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Kai Zou , Zhiwei Zhao , Bin Liu , Nenghai Yu

While foundation models (FMs), such as diffusion models and large vision-language models (LVLMs), have been widely applied in educational contexts, their ability to generate pedagogically effective visual explanations remains limited. Most…

Artificial Intelligence · Computer Science 2025-05-29 Haonian Ji , Shi Qiu , Siyang Xin , Siwei Han , Zhaorun Chen , Dake Zhang , Hongyi Wang , Huaxiu Yao

In this paper, we study video synthesis with emphasis on simplifying the generation conditions. Most existing video synthesis models or datasets are designed to address complex motions of a single object, lacking the ability of…

Computer Vision and Pattern Recognition · Computer Science 2023-05-24 Yang Wu , Zhibin Liu , Hefeng Wu , Liang Lin

Visual reasoning refers to the task of solving questions about visual information. Current visual reasoning methods typically employ pre-trained vision-language model (VLM) strategies or deep neural network approaches. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Chao Wang , Chunbai Zhang , Yongxiao Tian , Yang Zhou , Yan Peng

Recent advancements in leveraging pre-trained 2D diffusion models achieve the generation of high-quality novel views from a single in-the-wild image. However, existing works face challenges in producing controllable novel views due to the…

Computer Vision and Pattern Recognition · Computer Science 2025-07-04 Yunhan Yang , Shuo Chen , Yukun Huang , Xiaoyang Wu , Yuan-Chen Guo , Edmund Y. Lam , Hengshuang Zhao , Tong He , Xihui Liu

Recent Large Vision Language Models (LVLMs) demonstrate promising capabilities in unifying visual understanding and generative modeling, enabling both accurate content understanding and flexible editing. However, current approaches treat…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Fan Yang , Yousong Zhu , Xin Li , Yufei Zhan , Hongyin Zhao , Shurong Zheng , Yaowei Wang , Ming Tang , Jinqiao Wang

We present VQTalker, a Vector Quantization-based framework for multilingual talking head generation that addresses the challenges of lip synchronization and natural motion across diverse languages. Our approach is grounded in the phonetic…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Tao Liu , Ziyang Ma , Qi Chen , Feilong Chen , Shuai Fan , Xie Chen , Kai Yu

Artificial Intelligence Generated Content(AIGC), known for its superior visual results, represents a promising mitigation method for high-cost advertising applications. Numerous approaches have been developed to manipulate generated content…

Artificial Intelligence · Computer Science 2024-05-30 Shusong Xu , Peiye Liu

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

Scalable Vector Graphics (SVG) is a popular vector image format that offers good support for interactivity and animation. Despite its appealing characteristics, creating custom SVG content can be challenging for users due to the steep…

Computer Vision and Pattern Recognition · Computer Science 2023-06-08 Ronghuan Wu , Wanchao Su , Kede Ma , Jing Liao

With the rapid development of generative technology, current generative models can generate high-fidelity digital content and edit it in a controlled manner. However, there is a risk that malicious individuals might misuse these…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Junjie Cao , Kaizhou Li , Xinchun Yu , Hongxiang Li , Xiaoping Zhang

Video generation has witnessed significant advancements, yet evaluating these models remains a challenge. A comprehensive evaluation benchmark for video generation is indispensable for two reasons: 1) Existing metrics do not fully align…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Ziqi Huang , Fan Zhang , Xiaojie Xu , Yinan He , Jiashuo Yu , Ziyue Dong , Qianli Ma , Nattapol Chanpaisit , Chenyang Si , Yuming Jiang , Yaohui Wang , Xinyuan Chen , Ying-Cong Chen , Limin Wang , Dahua Lin , Yu Qiao , Ziwei Liu

Recent advances in audio-driven talking head generation have achieved impressive results in lip synchronization and emotional expression. However, they largely overlook the crucial task of facial attribute editing. This capability is…

Computer Vision and Pattern Recognition · Computer Science 2025-08-28 Guanwen Feng , Zhiyuan Ma , Yunan Li , Jiahao Yang , Junwei Jing , Qiguang Miao

Generating high-quality 360{\deg} panoramic videos from perspective input is one of the crucial applications for virtual reality (VR), whereby high-resolution videos are especially important for immersive experience. Existing methods are…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Lingen Li , Guangzhi Wang , Xiaoyu Li , Zhaoyang Zhang , Qi Dou , Jinwei Gu , Tianfan Xue , Ying Shan

With the rapid development of AI-generated content (AIGC), video generation has emerged as one of its most dynamic and impactful subfields. In particular, the advancement of video generation foundation models has led to growing demand for…