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Related papers: Can Image-To-Video Models Simulate Pedestrian Dyna…

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A simulation model for the dynamic behaviour of pedestrian crowds is mathematically formulated in terms of a social force model, that means, pedestrians behave in a way as if they would be subject to an acceleration force and to repulsive…

Statistical Mechanics · Physics 2007-05-23 D. Helbing , P. Molnar , F. Schweitzer

The progress on generative models has led to significant advances on text-to-video (T2V) generation, yet the motion controllability of generated videos remains limited. Existing motion transfer methods explored the motion representations of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Yufei Cai , Hu Han , Yuxiang Wei , Shiguang Shan , Xilin Chen

AI-assisted lesion detection models play a crucial role in the early screening of cancer. However, previous image-based models ignore the inter-frame contextual information present in videos. On the other hand, video-based models capture…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Yuncheng Jiang , Zixun Zhang , Jun Wei , Chun-Mei Feng , Guanbin Li , Xiang Wan , Shuguang Cui , Zhen Li

Diffusion models have made significant strides in image generation, mastering tasks such as unconditional image synthesis, text-image translation, and image-to-image conversions. However, their capability falls short in the realm of video…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Gaurav Shrivastava , Abhinav Shrivastava

The possibility to understand and to quantitatively model the physics of the interactions between pedestrians walking in crowds has compelling relevant applications, e.g. related to the design and safety of civil infrastructures. In this…

Physics and Society · Physics 2018-12-19 Alessandro Corbetta , Jasper Meeusen , Chung-min Lee , Roberto Benzi , Federico Toschi

With wearable IMU sensors, one can estimate human poses from wearable devices without requiring visual input~\cite{von2017sparse}. In this work, we pose the question: Can we reason about object structure in real-world environments solely…

Robotics · Computer Science 2022-07-15 Yinyu Nie , Angela Dai , Xiaoguang Han , Matthias Nießner

In this paper, we efficiently transfer the surpassing representation power of the vision foundation models, such as ViT and Swin, for video understanding with only a few trainable parameters. Previous adaptation methods have simultaneously…

Computer Vision and Pattern Recognition · Computer Science 2023-03-20 Jungin Park , Jiyoung Lee , Kwanghoon Sohn

Recent advances in diffusion-based text-to-video (T2V) models have demonstrated remarkable progress, but these models still face challenges in generating videos with multiple objects. Most models struggle with accurately capturing complex…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Aimon Rahman , Jiang Liu , Ze Wang , Ximeng Sun , Jialian Wu , Xiaodong Yu , Yusheng Su , Vishal M. Patel , Zicheng Liu , Emad Barsoum

Videos provide a rich source of information, but it is generally hard to extract dynamical parameters of interest. Inferring those parameters from a video stream would be beneficial for physical reasoning. Robots performing tasks in dynamic…

Text-to-video generation aims to produce a video based on a given prompt. Recently, several commercial video models have been able to generate plausible videos with minimal noise, excellent details, and high aesthetic scores. However, these…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Haoxin Chen , Yong Zhang , Xiaodong Cun , Menghan Xia , Xintao Wang , Chao Weng , Ying Shan

As recent advances in large-scale Text-to-Image (T2I) diffusion models have yielded remarkable high-quality image generation, diverse downstream Image-to-Image (I2I) applications have emerged. Despite the impressive results achieved by…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Geonung Kim , Beomsu Kim , Eunhyeok Park , Sunghyun Cho

High-quality video generation, encompassing text-to-video (T2V), image-to-video (I2V), and video-to-video (V2V) generation, holds considerable significance in content creation to benefit anyone express their inherent creativity in new ways…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Ailing Zeng , Yuhang Yang , Weidong Chen , Wei Liu

Predicting pedestrian motion trajectories is crucial for path planning and motion control of autonomous vehicles. Accurately forecasting crowd trajectories is challenging due to the uncertain nature of human motions in different…

Computer Vision and Pattern Recognition · Computer Science 2024-01-11 Yu Liu , Yuexin Zhang , Kunming Li , Yongliang Qiao , Stewart Worrall , You-Fu Li , He Kong

Predicting pedestrian motion is essential for developing socially-aware robots that interact in a crowded environment. While the natural visual perspective for a social interaction setting is an egocentric view, the majority of existing…

Computer Vision and Pattern Recognition · Computer Science 2023-03-03 Benjamin Stoler , Meghdeep Jana , Soonmin Hwang , Jean Oh

Generating realistic human videos remains a challenging task, with the most effective methods currently relying on a human motion sequence as a control signal. Existing approaches often use existing motion extracted from other videos, which…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Hsin-Ping Huang , Yang Zhou , Jui-Hsien Wang , Difan Liu , Feng Liu , Ming-Hsuan Yang , Zhan Xu

Understanding the behavior of road users is of vital importance for the development of trajectory prediction systems. In this context, the latest advances have focused on recurrent structures, establishing the social interaction between the…

Computer Vision and Pattern Recognition · Computer Science 2021-06-09 A. Quintanar , D. Fernández-Llorca , I. Parra , R. Izquierdo , M. A. Sotelo

The rapid rise of image-to-video (I2V) generation enables realistic videos to be created from a single image but also brings new forensic demands. Unlike static images, I2V content evolves over time, requiring forensics to move beyond 2D…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Yuzhuo Chen , Zehua Ma , Han Fang , Hengyi Wang , Guanjie Wang , Weiming Zhang

Despite remarkable achievements in video synthesis, achieving granular control over complex dynamics, such as nuanced movement among multiple interacting objects, still presents a significant hurdle for dynamic world modeling, compounded by…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Pengxiang Li , Kai Chen , Zhili Liu , Ruiyuan Gao , Lanqing Hong , Guo Zhou , Hua Yao , Dit-Yan Yeung , Huchuan Lu , Xu Jia

The rising demand for creating lifelike avatars in the digital realm has led to an increased need for generating high-quality human videos guided by textual descriptions and poses. We propose Dancing Avatar, designed to fabricate human…

Computer Vision and Pattern Recognition · Computer Science 2023-08-16 Bosheng Qin , Wentao Ye , Qifan Yu , Siliang Tang , Yueting Zhuang

Diffusion-based text-to-video generation (T2V) or image-to-video (I2V) generation have emerged as a prominent research focus. However, there exists a challenge in integrating the two generative paradigms into a unified model. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Xinyu Xiao , Binbin Yang , Tingtian Li , Yipeng Yu , Sen Lei
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