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Motion controllability is crucial in video synthesis. However, most previous methods are limited to single control types, and combining them often results in logical conflicts. In this paper, we propose a disentangled and unified framework,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Wanquan Feng , Tianhao Qi , Jiawei Liu , Mingzhen Sun , Pengqi Tu , Tianxiang Ma , Fei Dai , Songtao Zhao , Siyu Zhou , Qian He

Wheeled robots are highly efficient in human living environments. However, conventional wheeled designs, limited by degrees of freedom, struggle to meet varying footprint needs and achieve omnidirectional mobility. This paper proposes a…

Robotics · Computer Science 2024-12-17 Ziqi Zhao , Peijia Xie , Max Q. -H. Meng

Adopting omnidirectional Field of View (FoV) cameras in aerial robots vastly improves perception ability, significantly advancing aerial robotics's capabilities in inspection, reconstruction, and rescue tasks. However, such sensors also…

Robotics · Computer Science 2024-04-01 Peize Liu , Chen Feng , Yang Xu , Yan Ning , Hao Xu , Shaojie Shen

We propose a training-free and robust solution to offer camera movement control for off-the-shelf video diffusion models. Unlike previous work, our method does not require any supervised finetuning on camera-annotated datasets or…

Computer Vision and Pattern Recognition · Computer Science 2025-02-26 Chen Hou , Zhibo Chen

Recent works have sought to enhance the controllability and precision of text-driven motion generation. Some approaches leverage large language models (LLMs) to produce more detailed texts, while others incorporate global 3D coordinate…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Keming Shen , Bizhu Wu , Junliang Chen , Xiaoqin Wang , Linlin Shen

The rapid advancement of deep learning has intensified the need for comprehensive data for use by autonomous driving algorithms. High-quality datasets are crucial for the development of effective data-driven autonomous driving solutions.…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Lianqing Zheng , Long Yang , Qunshu Lin , Wenjin Ai , Minghao Liu , Shouyi Lu , Jianan Liu , Hongze Ren , Jingyue Mo , Xiaokai Bai , Jie Bai , Zhixiong Ma , Xichan Zhu

The synthesis of spatiotemporally coherent 4D content presents fundamental challenges in computer vision, requiring simultaneous modeling of high-fidelity spatial representations and physically plausible temporal dynamics. Current…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Xiaoyan Liu , Kangrui Li , Yuehao Song , Jiaxin Liu

We introduce UniReal, a unified framework designed to address various image generation and editing tasks. Existing solutions often vary by tasks, yet share fundamental principles: preserving consistency between inputs and outputs while…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Xi Chen , Zhifei Zhang , He Zhang , Yuqian Zhou , Soo Ye Kim , Qing Liu , Yijun Li , Jianming Zhang , Nanxuan Zhao , Yilin Wang , Hui Ding , Zhe Lin , Hengshuang Zhao

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

Despite substantial progress in text-to-video generation, achieving precise and flexible control over fine-grained spatiotemporal attributes remains a significant unresolved challenge in video generation research. To address these…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Xu Zhang , Hao Zhou , Haoming Qin , Xiaobin Lu , Jiaxing Yan , Guanzhong Wang , Zeyu Chen , Yi Liu

Advances in generative modeling have significantly enhanced digital content creation, extending from 2D images to complex 3D and 4D scenes. Despite substantial progress, producing high-fidelity and temporally consistent dynamic 4D content…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 DongFu Yin , Xiaotian Chen , Fei Richard Yu , Xuanchen Li , Xinhao Zhang

We have recently seen tremendous progress in realistic text-to-motion generation. Yet, the existing methods often fail or produce implausible motions with unseen text inputs, which limits the applications. In this paper, we present OMG, a…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Han Liang , Jiacheng Bao , Ruichi Zhang , Sihan Ren , Yuecheng Xu , Sibei Yang , Xin Chen , Jingyi Yu , Lan Xu

Recent advances in modeling 3D objects mostly rely on synthetic datasets due to the lack of large-scale realscanned 3D databases. To facilitate the development of 3D perception, reconstruction, and generation in the real world, we propose…

Computer Vision and Pattern Recognition · Computer Science 2023-04-12 Tong Wu , Jiarui Zhang , Xiao Fu , Yuxin Wang , Jiawei Ren , Liang Pan , Wayne Wu , Lei Yang , Jiaqi Wang , Chen Qian , Dahua Lin , Ziwei Liu

Generating high-fidelity, temporally consistent videos in autonomous driving scenarios faces a significant challenge, e.g. problematic maneuvers in corner cases. Despite recent video generation works are proposed to tackcle the mentioned…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Junpeng Jiang , Gangyi Hong , Lijun Zhou , Enhui Ma , Hengtong Hu , Xia Zhou , Jie Xiang , Fan Liu , Kaicheng Yu , Haiyang Sun , Kun Zhan , Peng Jia , Miao Zhang

In this work, we study Human-Object Interaction Video Generation (HOIVG), which aims to synthesize high-quality human-object interaction videos conditioned on text, reference images, audio, and pose. This task holds significant practical…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Donghao Zhou , Guisheng Liu , Hao Yang , Jiatong Li , Jingyu Lin , Xiaohu Huang , Yichen Liu , Xin Gao , Cunjian Chen , Shilei Wen , Chi-Wing Fu , Pheng-Ann Heng

Spatio-Temporal Video Grounding (STVG) aims to localize target objects in videos based on natural language descriptions. Despite recent advances in Multimodal Large Language Models, a significant gap remains between current models and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Hong Gao , Jingyu Wu , Xiangkai Xu , Kangni Xie , Yunchen Zhang , Bin Zhong , Xurui Gao , Min-Ling Zhang

In this paper, we propose spatio-temporal omni-object video grounding, dubbed OmniSTVG, a new STVG task that aims at localizing spatially and temporally all targets mentioned in the textual query from videos. Compared to classic STVG…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Jiali Yao , Xinran Deng , Xin Gu , Mengrui Dai , Bing Fan , Zhipeng Zhang , Yan Huang , Heng Fan , Libo Zhang

Recently, several point-based image editing methods (e.g., DragDiffusion, FreeDrag, DragNoise) have emerged, yielding precise and high-quality results based on user instructions. However, these methods often make insufficient use of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 DuoSheng Chen , Binghui Chen , Yifeng Geng , Liefeng Bo

We consider the problem of text-to-video generation tasks with precise control for various applications such as camera movement control and video-to-video editing. Most methods tacking this problem rely on providing user-defined controls,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Mathis Koroglu , Hugo Caselles-Dupré , Guillaume Jeanneret Sanmiguel , Matthieu Cord

Customized generation using diffusion models has made impressive progress in image generation, but remains unsatisfactory in the challenging video generation task, as it requires the controllability of both subjects and motions. To that…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Yujie Wei , Shiwei Zhang , Zhiwu Qing , Hangjie Yuan , Zhiheng Liu , Yu Liu , Yingya Zhang , Jingren Zhou , Hongming Shan