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Related papers: DragAnything: Motion Control for Anything using En…

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In recent years, diffusion models have achieved tremendous success in the field of video generation, with controllable video generation receiving significant attention. However, existing control methods still face two limitations: Firstly,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Zhang Wan , Sheng Tang , Jiawei Wei , Ruize Zhang , Juan Cao

This paper aims to manipulate multi-entity 3D motions in video generation. Previous methods on controllable video generation primarily leverage 2D control signals to manipulate object motions and have achieved remarkable synthesis results.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Xiao Fu , Xian Liu , Xintao Wang , Sida Peng , Menghan Xia , Xiaoyu Shi , Ziyang Yuan , Pengfei Wan , Di Zhang , Dahua Lin

Effective spatio-temporal representation is fundamental to modeling, understanding, and predicting dynamics in videos. The atomic unit of a video, the pixel, traces a continuous 3D trajectory over time, serving as the primitive element of…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Xinhang Liu , Yuxi Xiao , Donny Y. Chen , Jiashi Feng , Yu-Wing Tai , Chi-Keung Tang , Bingyi Kang

Pose-guided video generation refers to controlling the motion of subjects in generated video through a sequence of poses. It enables precise control over subject motion and has important applications in animation. However, current…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Ruiyan Wang , Teng Hu , Kaihui Huang , Zihan Su , Ran Yi , Lizhuang Ma

Synthesizing visual content that meets users' needs often requires flexible and precise controllability of the pose, shape, expression, and layout of the generated objects. Existing approaches gain controllability of generative adversarial…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Xingang Pan , Ayush Tewari , Thomas Leimkühler , Lingjie Liu , Abhimitra Meka , Christian Theobalt

We present a unified controllable video generation approach AnimateAnything that facilitates precise and consistent video manipulation across various conditions, including camera trajectories, text prompts, and user motion annotations.…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Guojun Lei , Chi Wang , Hong Li , Rong Zhang , Yikai Wang , Weiwei Xu

Conditional motion generation has been extensively studied in computer vision, yet two critical challenges remain. First, while masked autoregressive methods have recently outperformed diffusion-based approaches, existing masking models…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Zeyu Zhang , Yiran Wang , Wei Mao , Danning Li , Rui Zhao , Biao Wu , Zirui Song , Bohan Zhuang , Ian Reid , Richard Hartley

We present a method for controlling a simulated humanoid to grasp an object and move it to follow an object's trajectory. Due to the challenges in controlling a humanoid with dexterous hands, prior methods often use a disembodied hand and…

Robotics · Computer Science 2025-05-20 Zhengyi Luo , Jinkun Cao , Sammy Christen , Alexander Winkler , Kris Kitani , Weipeng Xu

We tackle the challenges of synthesizing versatile, physically simulated human motions for full-body object manipulation. Unlike prior methods that are focused on detailed motion tracking, trajectory following, or teleoperation, our…

Robotics · Computer Science 2025-12-12 Chen Tessler , Yifeng Jiang , Erwin Coumans , Zhengyi Luo , Gal Chechik , Xue Bin Peng

Mobile manipulation is a fundamental capability that enables robots to interact in expansive environments such as homes and factories. Most existing approaches follow a two-stage paradigm, where the robot first navigates to a docking point…

Robotics · Computer Science 2026-04-17 Ziyu Shan , Yuheng Zhou , Gaoyuan Wu , Ziheng Ji , Zhenyu Wu , Ziwei Wang

The intuitive nature of drag-based interaction has led to its growing adoption for controlling object trajectories in image-to-video synthesis. Still, existing methods that perform dragging in the 2D space usually face ambiguity when…

Computer Vision and Pattern Recognition · Computer Science 2025-03-31 Hanlin Wang , Hao Ouyang , Qiuyu Wang , Wen Wang , Ka Leong Cheng , Qifeng Chen , Yujun Shen , Limin Wang

Predicting the dynamics of interacting objects is essential for both humans and intelligent systems. However, existing approaches are limited to simplified, toy settings and lack generalizability to complex, real-world environments. Recent…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Rick Akkerman , Haiwen Feng , Michael J. Black , Dimitrios Tzionas , Victoria Fernández Abrevaya

We introduce DragAPart, a method that, given an image and a set of drags as input, generates a new image of the same object that responds to the action of the drags. Differently from prior works that focused on repositioning objects,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Ruining Li , Chuanxia Zheng , Christian Rupprecht , Andrea Vedaldi

We propose a unified framework for motion control in video generation that seamlessly integrates camera movement, object-level translation, and fine-grained local motion using trajectory-based inputs. In contrast to prior methods that…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Angtian Wang , Haibin Huang , Jacob Zhiyuan Fang , Yiding Yang , Chongyang Ma

Controllable video generation has gained significant attention in recent years. However, two main limitations persist: Firstly, most existing works focus on either text, image, or trajectory-based control, leading to an inability to achieve…

Computer Vision and Pattern Recognition · Computer Science 2023-08-17 Shengming Yin , Chenfei Wu , Jian Liang , Jie Shi , Houqiang Li , Gong Ming , Nan Duan

This paper addresses the problem of enabling a robot to represent and recreate visual information through physical motion, focusing on drawing using pens, brushes, or other tools. This work uses ergodicity as a control objective that…

Robotics · Computer Science 2018-08-29 Ahalya Prabhakar , Anastasia Mavrommati , Jarvis Schultz , Todd Murphey

Large-scale endeavors like and widespread community efforts such as Open-X-Embodiment have contributed to growing the scale of robot demonstration data. However, there is still an opportunity to improve the quality, quantity, and diversity…

Robotics · Computer Science 2024-08-30 Jiafei Duan , Wentao Yuan , Wilbert Pumacay , Yi Ru Wang , Kiana Ehsani , Dieter Fox , Ranjay Krishna

Tracking and following objects of interest is critical to several robotics use cases, ranging from industrial automation to logistics and warehousing, to healthcare and security. In this paper, we present a robotic system to detect, track,…

Motions in a video primarily consist of camera motion, induced by camera movement, and object motion, resulting from object movement. Accurate control of both camera and object motion is essential for video generation. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Zhouxia Wang , Ziyang Yuan , Xintao Wang , Tianshui Chen , Menghan Xia , Ping Luo , Ying Shan

To achieve pixel-level image manipulation, drag-style image editing which edits images using points or trajectories as conditions is attracting widespread attention. Most previous methods follow move-and-track framework, in which miss…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Jiacheng Sui , Yujie Zhou , Li Niu
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