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Automatic 3D generation has recently attracted widespread attention. Recent methods have greatly accelerated the generation speed, but usually produce less-detailed objects due to limited model capacity or 3D data. Motivated by recent…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Zilong Chen , Yikai Wang , Feng Wang , Zhengyi Wang , Huaping Liu

We introduce LivingWorld, an interactive framework for generating 4D worlds with environmental dynamics from a single image. While recent advances in 3D scene generation enable large-scale environment creation, most approaches focus…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Hyeongju Mun , In-Hwan Jin , Sohyeong Kim , Kyeongbo Kong

Generative models have shown great promise in generating 3D geometric systems, which is a fundamental problem in many natural science domains such as molecule and protein design. However, existing approaches only operate on static…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Jiaqi Han , Minkai Xu , Aaron Lou , Haotian Ye , Stefano Ermon

Localization is a key challenge in many robotics applications. In this work we explore LIDAR-based global localization in both urban and natural environments and develop a method suitable for online application. Our approach leverages…

Robotics · Computer Science 2023-02-01 Georgi Tinchev , Adrian Penate-Sanchez , Maurice Fallon

We introduce Efficient Motion Diffusion Model (EMDM) for fast and high-quality human motion generation. Current state-of-the-art generative diffusion models have produced impressive results but struggle to achieve fast generation without…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Wenyang Zhou , Zhiyang Dou , Zeyu Cao , Zhouyingcheng Liao , Jingbo Wang , Wenjia Wang , Yuan Liu , Taku Komura , Wenping Wang , Lingjie Liu

Understanding and predicting dynamics of the physical world can enhance a robot's ability to plan and interact effectively in complex environments. While recent video generation models have shown strong potential in modeling dynamic scenes,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Zeyi Liu , Shuang Li , Eric Cousineau , Siyuan Feng , Benjamin Burchfiel , Shuran Song

World models have become crucial for autonomous driving, as they learn how scenarios evolve over time to address the long-tail challenges of the real world. However, current approaches relegate world models to limited roles: they operate…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Tianze Xia , Yongkang Li , Lijun Zhou , Jingfeng Yao , Kaixin Xiong , Haiyang Sun , Bing Wang , Kun Ma , Guang Chen , Hangjun Ye , Wenyu Liu , Xinggang Wang

One key vertical application that will be enabled by 6G is the automation of the processes with the increased use of robots. As a result, sensing and localization of the surrounding environment becomes a crucial factor for these robots to…

Signal Processing · Electrical Eng. & Systems 2021-02-23 Madhushanka Padmal , Dileepa Marasinghe , Vijitha Isuru , Nalin Jayaweera , Samad Ali , Nandana Rajatheva

The 3D object detection capabilities in urban environments have been enormously improved by recent developments in Light Detection and Range (LiDAR) technology. This paper presents a novel framework that transforms the detection and…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Nawfal Guefrachi , Hakim Ghazzai , Ahmad Alsharoa

Generating sewing patterns in garment design is receiving increasing attention due to its CG-friendly and flexible-editing nature. Previous sewing pattern generation methods have been able to produce exquisite clothing, but struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Shengqi Liu , Yuhao Cheng , Zhuo Chen , Xingyu Ren , Wenhan Zhu , Lincheng Li , Mengxiao Bi , Xiaokang Yang , Yichao Yan

World models have demonstrated superiority in autonomous driving, particularly in the generation of multi-view driving videos. However, significant challenges still exist in generating customized driving videos. In this paper, we propose…

Computer Vision and Pattern Recognition · Computer Science 2024-04-12 Guosheng Zhao , Xiaofeng Wang , Zheng Zhu , Xinze Chen , Guan Huang , Xiaoyi Bao , Xingang Wang

Generating temporally coherent high fidelity video is an important milestone in generative modeling research. We make progress towards this milestone by proposing a diffusion model for video generation that shows very promising initial…

Computer Vision and Pattern Recognition · Computer Science 2022-06-24 Jonathan Ho , Tim Salimans , Alexey Gritsenko , William Chan , Mohammad Norouzi , David J. Fleet

With the rapid advancement of autonomous driving technology, a lack of data has become a major obstacle to enhancing perception model accuracy. Researchers are now exploring controllable data generation using world models to diversify…

Computer Vision and Pattern Recognition · Computer Science 2025-06-27 Xinqing Li , Ruiqi Song , Qingyu Xie , Ye Wu , Nanxin Zeng , Yunfeng Ai

We present 4DNeX, the first feed-forward framework for generating 4D (i.e., dynamic 3D) scene representations from a single image. In contrast to existing methods that rely on computationally intensive optimization or require multi-frame…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Zhaoxi Chen , Tianqi Liu , Long Zhuo , Jiawei Ren , Zeng Tao , He Zhu , Fangzhou Hong , Liang Pan , Ziwei Liu

In Autonomous Driving (AD), detection and tracking of obstacles on the roads is a critical task. Deep-learning based methods using annotated LiDAR data have been the most widely adopted approach for this. Unfortunately, annotating 3D point…

Computer Vision and Pattern Recognition · Computer Science 2021-07-02 Jin Fang , Dingfu Zhou , Feilong Yan , Tongtong Zhao , Feihu Zhang , Yu Ma , Liang Wang , Ruigang Yang

LiDAR scene synthesis is an emerging solution to scarcity in 3D data for robotic tasks such as autonomous driving. Recent approaches employ diffusion or flow matching models to generate realistic scenes, but 3D data remains limited compared…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Nicolas Sereyjol-Garros , Ellington Kirby , Victor Besnier , Nermin Samet

Mapping the environment has been an important task for robot navigation and Simultaneous Localization And Mapping (SLAM). LIDAR provides a fast and accurate 3D point cloud map of the environment which helps in map building. However,…

Computer Vision and Pattern Recognition · Computer Science 2020-06-14 Aritra Mukherjee , Sourya Dipta Das , Jasorsi Ghosh , Ananda S. Chowdhury , Sanjoy Kumar Saha

Recently, diffusion models have demonstrated impressive capabilities in text-guided and image-conditioned image generation. However, existing diffusion models cannot simultaneously generate an image and a panoptic segmentation of objects…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Yinghan Long , Kaushik Roy

Controllable generation is considered a potentially vital approach to address the challenge of annotating 3D data, and the precision of such controllable generation becomes particularly imperative in the context of data production for…

Computer Vision and Pattern Recognition · Computer Science 2025-07-16 Jinhua Zhang , Hualian Sheng , Sijia Cai , Bing Deng , Qiao Liang , Wen Li , Ying Fu , Jieping Ye , Shuhang Gu

With the increasing popularity of autonomous driving based on the powerful and unified bird's-eye-view (BEV) representation, a demand for high-quality and large-scale multi-view video data with accurate annotation is urgently required.…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Xiaofan Li , Yifu Zhang , Xiaoqing Ye