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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 achieved remarkable progress with the introduction of diffusion models, which have significantly improved the quality of generated videos. However, recent research has primarily focused on scaling up model training,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Chenyang Si , Weichen Fan , Zhengyao Lv , Ziqi Huang , Yu Qiao , Ziwei Liu

Recent advancements in autonomous driving (AD) systems have highlighted the potential of world models in achieving robust and generalizable performance across both ordinary and challenging driving conditions. However, a key challenge…

Computer Vision and Pattern Recognition · Computer Science 2025-07-21 Bu Jin , Weize Li , Baihan Yang , Zhenxin Zhu , Junpeng Jiang , Huan-ang Gao , Haiyang Sun , Kun Zhan , Hengtong Hu , Xueyang Zhang , Peng Jia , Hao Zhao

Image composition plays an important role in the quality of a photo. However, not every camera user possesses the knowledge and expertise required for capturing well-composed photos. While post-capture cropping can improve the composition…

Computer Vision and Pattern Recognition · Computer Science 2021-04-16 Yu-Chuan Su , Raviteja Vemulapalli , Ben Weiss , Chun-Te Chu , Philip Andrew Mansfield , Lior Shapira , Colvin Pitts

Shot transitions play a pivotal role in multi-shot video generation, as they determine the overall narrative expression and the directorial design of visual storytelling. However, recent progress has primarily focused on low-level visual…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Xiaoxue Wu , Xinyuan Chen , Yaohui Wang , Yu Qiao

Following the advancements in text-guided image generation technology exemplified by Stable Diffusion, video generation is gaining increased attention in the academic community. However, relying solely on text guidance for video generation…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Cong Wang , Jiaxi Gu , Panwen Hu , Haoyu Zhao , Yuanfan Guo , Jianhua Han , Hang Xu , Xiaodan Liang

Despite significant advances in video synthesis, research into multi-shot video generation remains in its infancy. Even with scaled-up models and massive datasets, the shot transition capabilities remain rudimentary and unstable, largely…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Xiaoxue Wu , Bingjie Gao , Yu Qiao , Yaohui Wang , Xinyuan Chen

Prior methods for controlling image generation are limited in their ability to be taught new tasks. In contrast, vision-language models, or VLMs, can learn tasks in-context and produce the correct outputs for a given input. We propose a…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Grace Luo , Jonathan Granskog , Aleksander Holynski , Trevor Darrell

Diffusion models have made significant advances in generating high-quality images, but their application to video generation has remained challenging due to the complexity of temporal motion. Zero-shot video editing offers a solution by…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Xirui Li , Chao Ma , Xiaokang Yang , Ming-Hsuan Yang

Existing two-stream models, such as CLIP, encode images and text through independent representations, showing good performance while ensuring retrieval speed, have attracted attention from industry and academia. However, the single…

Computer Vision and Pattern Recognition · Computer Science 2025-02-20 Wanqing Cui , Rui Cheng , Jiafeng Guo , Xueqi Cheng

Text-editable and pose-controllable character video generation is a challenging but prevailing topic with practical applications. However, existing approaches mainly focus on single-object video generation with pose guidance, ignoring the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Beiyuan Zhang , Yue Ma , Chunlei Fu , Xinyang Song , Zhenan Sun , Ziqiang Li

Recent advances in video diffusion transformers have enabled interactive gaming world models that allow users to explore generated environments over extended horizons. However, existing approaches struggle with precise action control and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Jisu Nam , Yicong Hong , Chun-Hao Paul Huang , Feng Liu , JoungBin Lee , Jiyoung Kim , Siyoon Jin , Yunsung Lee , Jaeyoon Jung , Suhwan Choi , Seungryong Kim , Yang Zhou

Scene rearrangement, like table tidying, is a challenging task in robotic manipulation due to the complexity of predicting diverse object arrangements. Web-scale trained generative models such as Stable Diffusion can aid by generating…

Robotics · Computer Science 2024-12-03 Shutong Jin , Ruiyu Wang , Kuangyi Chen , Florian T. Pokorny

Live-streaming Novel View Synthesis (NVS) from unposed multi-view video remains an open challenge in a wide range of applications. Existing methods for dynamic scene representation typically require ground-truth camera parameters and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Pedro Quesado , Erkut Akdag , Yasaman Kashefbahrami , Willem Menu , Egor Bondarev

Text-to-video diffusion models have advanced video generation significantly. However, customizing these models to generate videos with tailored motions presents a substantial challenge. In specific, they encounter hurdles in (a) accurately…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Hyeonho Jeong , Geon Yeong Park , Jong Chul Ye

This paper presents a method that allows users to design cinematic video shots in the context of image-to-video generation. Shot design, a critical aspect of filmmaking, involves meticulously planning both camera movements and object…

Computer Vision and Pattern Recognition · Computer Science 2025-02-07 Jinbo Xing , Long Mai , Cusuh Ham , Jiahui Huang , Aniruddha Mahapatra , Chi-Wing Fu , Tien-Tsin Wong , Feng Liu

Anticipating future actions based on spatiotemporal observations is essential in video understanding and predictive computer vision. Moreover, a model capable of anticipating the future has important applications, it can benefit…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Tsung-Ming Tai , Giuseppe Fiameni , Cheng-Kuang Lee , Simon See , Oswald Lanz

With the advancement of generative artificial intelligence, previous studies have achieved the task of generating aesthetic images from hand-drawn sketches, fulfilling the public's needs for drawing. However, these methods are limited to…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Lifan Jiang , Shuang Chen , Boxi Wu , Xiaotong Guan , Jiahui Zhang

We present TrajectoryCrafter, a novel approach to redirect camera trajectories for monocular videos. By disentangling deterministic view transformations from stochastic content generation, our method achieves precise control over…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Mark YU , Wenbo Hu , Jinbo Xing , Ying Shan

Image composition targets at synthesizing a realistic composite image from a pair of foreground and background images. Recently, generative composition methods are built on large pretrained diffusion models to generate composite images,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Bo Zhang , Yuxuan Duan , Jun Lan , Yan Hong , Huijia Zhu , Weiqiang Wang , Li Niu