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Controllable scene synthesis consists of generating 3D information that satisfy underlying specifications. Thereby, these specifications should be abstract, i.e. allowing easy user interaction, whilst providing enough interface for detailed…

Computer Vision and Pattern Recognition · Computer Science 2021-08-20 Helisa Dhamo , Fabian Manhardt , Nassir Navab , Federico Tombari

Driving video generation has achieved much progress in controllability, video resolution, and length, but fails to support fine-grained object-level controllability for diverse driving videos, while preserving the spatiotemporal…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Li-Heng Chen , Ke Cheng , Yahui Liu , Lei Shi , Shi-Sheng Huang , Hongbo Fu

Generating realistic 3D indoor scenes from user inputs remains a challenging problem in computer vision and graphics, requiring careful balance of geometric consistency, spatial relationships, and visual realism. While neural generation…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Mengqi Zhou , Xipeng Wang , Yuxi Wang , Zhaoxiang Zhang

Realistic and diverse traffic scenarios in large quantities are crucial for the development and validation of autonomous driving systems. However, owing to numerous difficulties in the data collection process and the reliance on intensive…

Robotics · Computer Science 2025-10-07 Shuo Sun , Zekai Gu , Tianchen Sun , Jiawei Sun , Chengran Yuan , Yuhang Han , Dongen Li , Marcelo H. Ang

We present an integrated approach for perception and control for an autonomous vehicle and demonstrate this approach in a high-fidelity urban driving simulator. Our approach first builds a model for the environment, then trains a policy…

Systems and Control · Electrical Eng. & Systems 2020-03-19 Ali Baheri , Ilya Kolmanovsky , Anouck Girard , H. Eric Tseng , Dimitar Filev

Dashboard cameras capture a tremendous amount of driving scene video each day. These videos are purposefully coupled with vehicle sensing data, such as from the speedometer and inertial sensors, providing an additional sensing modality for…

Computer Vision and Pattern Recognition · Computer Science 2019-09-17 Seokju Lee , Junsik Kim , Tae-Hyun Oh , Yongseop Jeong , Donggeun Yoo , Stephen Lin , In So Kweon

Generating realistic and interactive dynamics of traffic participants according to specific instruction is critical for street scene simulation. However, there is currently a lack of a comprehensive method that generates realistic dynamics…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Yuxi Wei , Jingbo Wang , Yuwen Du , Dingju Wang , Liang Pan , Chenxin Xu , Yao Feng , Bo Dai , Siheng Chen

Generating visual text in natural scene images is a challenging task with many unsolved problems. Different from generating text on artificially designed images (such as posters, covers, cartoons, etc.), the text in natural scene images…

Computer Vision and Pattern Recognition · Computer Science 2025-01-08 Jiawei Liu , Yuanzhi Zhu , Feiyu Gao , Zhibo Yang , Peng Wang , Junyang Lin , Xinggang Wang , Wenyu Liu

3D visual grounding aims to localize the unique target described by natural languages in 3D scenes. The significant gap between 3D and language modalities makes it a notable challenge to distinguish multiple similar objects through the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Feng Xiao , Hongbin Xu , Guocan Zhao , Wenxiong Kang

Generating safety-critical scenarios is essential for testing and verifying the safety of autonomous vehicles. Traditional optimization techniques suffer from the curse of dimensionality and limit the search space to fixed parameter spaces.…

Machine Learning · Computer Science 2024-03-08 Haolan Liu , Liangjun Zhang , Siva Kumar Sastry Hari , Jishen Zhao

Traffic scene understanding is essential for enabling autonomous vehicles to accurately perceive and interpret their environment, thereby ensuring safe navigation. This paper presents a novel framework that transforms a single frontal-view…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Danial Sadrian Zadeh , Otman A. Basir , Behzad Moshiri

Recent advances in text-to-3D scene generation have demonstrated significant potential to transform content creation across multiple industries. Although the research community has made impressive progress in addressing the challenges of…

Large-scale labelled driving video data is essential for training autonomous driving systems. Although simulation offers scalable and fully annotated data, the domain gap between synthetic and real-world driving videos significantly limits…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Haonan Zhao , Yiting Wang , Jingkun Chen , Valentina Donzella , Thomas Bashford-Rogers , Kurt Debattista

Camera control has been actively studied in text or image conditioned video generation tasks. However, altering camera trajectories of a given video remains under-explored, despite its importance in the field of video creation. It is…

Computer Vision and Pattern Recognition · Computer Science 2025-07-10 Jianhong Bai , Menghan Xia , Xiao Fu , Xintao Wang , Lianrui Mu , Jinwen Cao , Zuozhu Liu , Haoji Hu , Xiang Bai , Pengfei Wan , Di Zhang

We introduce SceneLinker, a novel framework that generates compositional 3D scenes via semantic scene graph from RGB sequences. To adaptively experience Mixed Reality (MR) content based on each user's space, it is essential to generate a 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Seok-Young Kim , Dooyoung Kim , Woojin Cho , Hail Song , Suji Kang , Woontack Woo

We propose a method for generating fly-through videos of a scene, from a single image and a given camera trajectory. We build upon an image-to-video latent diffusion model. We condition its UNet denoiser on the camera trajectory, using four…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Stefan Popov , Amit Raj , Michael Krainin , Yuanzhen Li , William T. Freeman , Michael Rubinstein

We introduce Drag4D, an interactive framework that integrates object motion control within text-driven 3D scene generation. This framework enables users to define 3D trajectories for the 3D objects generated from a single image, seamlessly…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Minjun Kang , Inkyu Shin , Taeyeop Lee , In So Kweon , Kuk-Jin Yoon

We propose a novel task of text-controlled human object interaction generation in 3D scenes with movable objects. Existing human-scene interaction datasets suffer from insufficient interaction categories and typically only consider…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Xinhao Cai , Minghang Zheng , Xin Jin , Yang Liu

In order to offer a customized script tool and inspire professional scriptwriters, we present VScript. It is a controllable pipeline that generates complete scripts, including dialogues and scene descriptions, as well as presents visually…

Computation and Language · Computer Science 2022-11-24 Ziwei Ji , Yan Xu , I-Tsun Cheng , Samuel Cahyawijaya , Rita Frieske , Etsuko Ishii , Min Zeng , Andrea Madotto , Pascale Fung

End-to-end autonomous driving aims to generate safe and plausible planning policies from raw sensor input. Driving world models have shown great potential in learning rich representations by predicting the future evolution of a driving…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Xingtai Gui , Meijie Zhang , Tianyi Yan , Wencheng Han , Jiahao Gong , Feiyang Tan , Cheng-zhong Xu , Jianbing Shen
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