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Learning 4D language fields to enable time-sensitive, open-ended language queries in dynamic scenes is essential for many real-world applications. While LangSplat successfully grounds CLIP features into 3D Gaussian representations,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Wanhua Li , Renping Zhou , Jiawei Zhou , Yingwei Song , Johannes Herter , Minghan Qin , Gao Huang , Hanspeter Pfister

We present LidarDM, a novel LiDAR generative model capable of producing realistic, layout-aware, physically plausible, and temporally coherent LiDAR videos. LidarDM stands out with two unprecedented capabilities in LiDAR generative…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Vlas Zyrianov , Henry Che , Zhijian Liu , Shenlong Wang

Physics-aware driving world model is essential for drive planning, out-of-distribution data synthesis, and closed-loop evaluation. However, existing methods often rely on a single diffusion model to directly map driving actions to videos,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Zhenya Yang , Zhe Liu , Yuxiang Lu , Liping Hou , Chenxuan Miao , Siyi Peng , Bailan Feng , Xiang Bai , Hengshuang Zhao

Recently, the surge of efficient and automated 3D AI-generated content (AIGC) methods has increasingly illuminated the path of transforming human imagination into complex 3D structures. However, the automated generation of 3D content is…

Graphics · Computer Science 2024-12-20 Pei Chen , Fudong Wang , Yixuan Tong , Jingdong Chen , Ming Yang , Minghui Yang

We introduce ScenarioControl, the first vision-language control mechanism for learned driving scenario generation. Given a text prompt or an input image, Scenario-Control synthesizes diverse, realistic 3D scenario rollouts - including map,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Lili Gao , Yanbo Xu , William Koch , Samuele Ruffino , Luke Rowe , Behdad Chalaki , Dmitriy Rivkin , Julian Ost , Roger Girgis , Mario Bijelic , Felix Heide

3D world models (i.e., learning-based 3D dynamics models) offer a promising approach to generalizable robotic manipulation by capturing the underlying physics of environment evolution conditioned on robot actions. However, existing 3D world…

Robotics · Computer Science 2025-08-27 Suning Huang , Qianzhong Chen , Xiaohan Zhang , Jiankai Sun , Mac Schwager

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

Recent advancements in personalized Text-to-Video (T2V) generation have made significant strides in synthesizing character-specific content. However, these methods face a critical limitation: the inability to perform fine-grained control…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Haopeng Fang , Di Qiu , Binjie Mao , He Tang

This paper presents ShareVerse, a video generation framework enabling multi-agent shared world modeling, addressing the gap in existing works that lack support for unified shared world construction with multi-agent interaction. ShareVerse…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Jiayi Zhu , Jianing Zhang , Yiying Yang , Wei Cheng , Xiaoyun Yuan

Controllability plays a crucial role in video generation, as it allows users to create and edit content more precisely. Existing models, however, lack control of camera pose that serves as a cinematic language to express deeper narrative…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Hao He , Yinghao Xu , Yuwei Guo , Gordon Wetzstein , Bo Dai , Hongsheng Li , Ceyuan Yang

Video Motion Magnification (VMM) reveals imperceptible dynamics but often suffers from structural inconsistencies under complex geometric transformations. Existing learning-based methods generally face a trade-off between the limited global…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Kecheng Han , Yuchen Zhang , Bingqing Liu , Boqiang Guo , Wenbin Zheng , Shiyuan Pei

This paper aims to tackle the challenge of dynamic view synthesis from multi-view videos. The key observation is that while previous grid-based methods offer consistent rendering, they fall short in capturing appearance details of a complex…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Haotong Lin , Sida Peng , Zhen Xu , Tao Xie , Xingyi He , Hujun Bao , Xiaowei Zhou

Achieving seamless viewing of high-fidelity volumetric video, comparable to 2D video experiences, remains an open challenge. Existing volumetric video compression methods either lack the flexibility to adjust quality and bitrate within a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Zihan Zheng , Zhenlong Wu , Houqiang Zhong , Yuan Tian , Ning Cao , Lan Xu , Jiangchao Yao , Xiaoyun Zhang , Qiang Hu , Wenjun Zhang

We present PanoWorld, a panoramic video world model that generates geometry-consistent 360$\degree$ video from a single image and a caption. Existing panoramic video methods optimize primarily for visual realism and do not explicitly…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Le Jiang , Xiangyu Bai , Bishoy Galoaa , Shayda Moezzi , Caleb James Lee , Tooba Imtiaz , Edmund Yeh , Jennifer Dy , Yanzhi Wang , Sarah Ostadabbas

Recent progress in robot learning has been driven by large-scale datasets and powerful visuomotor policy architectures, yet policy robustness remains limited by the substantial cost of collecting diverse demonstrations, particularly for…

Robotics · Computer Science 2026-03-24 Yujie Zhao , Hongwei Fan , Di Chen , Shengcong Chen , Liliang Chen , Xiaoqi Li , Guanghui Ren , Hao Dong

360{\deg} videos have emerged as a promising medium to represent our dynamic visual world. Compared to the "tunnel vision" of standard cameras, their borderless field of view offers a more complete perspective of our surroundings. While…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Rundong Luo , Matthew Wallingford , Ali Farhadi , Noah Snavely , Wei-Chiu Ma

Recent advancements in video generation have enabled the development of ``world models'' capable of simulating potential futures for robotics and planning. However, specifying precise goals for these models remains a challenge; text…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Nate Gillman , Yinghua Zhou , Zitian Tang , Evan Luo , Arjan Chakravarthy , Daksh Aggarwal , Michael Freeman , Charles Herrmann , Chen Sun

The synthesis of immersive 3D scenes from text is rapidly maturing, driven by novel video generative models and feed-forward 3D reconstruction, with vast potential in AR/VR and world modeling. While panoramic images have proven effective…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Felix Wimbauer , Fabian Manhardt , Michael Oechsle , Nikolai Kalischek , Christian Rupprecht , Daniel Cremers , Federico Tombari

Corner cases are crucial for training and validating autonomous driving systems, yet collecting them from the real world is often costly and hazardous. Editing objects within captured sensor data offers an effective alternative for…

Computer Vision and Pattern Recognition · Computer Science 2025-08-29 Jiusi Li , Jackson Jiang , Jinyu Miao , Miao Long , Tuopu Wen , Peijin Jia , Shengxiang Liu , Chunlei Yu , Maolin Liu , Yuzhan Cai , Kun Jiang , Mengmeng Yang , Diange Yang

The generation of sounding videos has seen significant advancements with the advent of diffusion models. However, existing methods often lack the fine-grained control needed to generate viewpoint-specific content from larger, immersive…