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Generating articulated assets is crucial for robotics, digital twins, and embodied intelligence. Existing generative models often rely on single-view inputs representing closed states, resulting in ambiguous or unrealistic kinematic…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Haowen Wang , Xiaoping Yuan , Fugang Zhang , Rui Jian , Yuanwei Zhu , Xiuquan Qiao , Yakun Huang

We introduce ART, Articulated Reconstruction Transformer -- a category-agnostic, feed-forward model that reconstructs complete 3D articulated objects from only sparse, multi-state RGB images. Previous methods for articulated object…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Zizhang Li , Cheng Zhang , Zhengqin Li , Henry Howard-Jenkins , Zhaoyang Lv , Chen Geng , Jiajun Wu , Richard Newcombe , Jakob Engel , Zhao Dong

Human-object interactions with articulated objects are common in everyday life. Despite much progress in single-view 3D reconstruction, it is still challenging to infer an articulated 3D object model from an RGB video showing a person…

Computer Vision and Pattern Recognition · Computer Science 2022-09-14 Sanjay Haresh , Xiaohao Sun , Hanxiao Jiang , Angel X. Chang , Manolis Savva

Robots operating in domestic environments generally need to interact with articulated objects, such as doors, cabinets, dishwashers or fridges. In this work, we present a novel, probabilistic framework for modeling articulated objects as…

Robotics · Computer Science 2014-06-02 Jürgen Sturm , Cyrill Stachniss , Wolfram Burgard

Scene graphs provide a rich, structured representation of a scene by encoding the entities (objects) and their spatial relationships in a graphical format. This representation has proven useful in several tasks, such as question answering,…

Computer Vision and Pattern Recognition · Computer Science 2022-12-01 Sanjoy Kundu , Sathyanarayanan N. Aakur

Learning descriptive 3D features is crucial for understanding 3D scenes with diverse objects and complex structures. However, it is usually unknown whether important geometric attributes and scene context obtain enough emphasis in an…

Computer Vision and Pattern Recognition · Computer Science 2022-12-13 Junbo Zhang , Guofan Fan , Guanghan Wang , Zhengyuan Su , Kaisheng Ma , Li Yi

This paper presents a novel framework for modeling and conditional generation of 3D articulated objects. Troubled by flexibility-quality tradeoffs, existing methods are often limited to using predefined structures or retrieving shapes from…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Jiayi Su , Youhe Feng , Zheng Li , Jinhua Song , Yangfan He , Botao Ren , Botian Xu

Articulated objects pose diverse manipulation challenges for robots. Since their internal structures are not directly observable, robots must adaptively explore and refine actions to generate successful manipulation trajectories. While…

Robotics · Computer Science 2025-07-25 Xiaojie Zhang , Yuanfei Wang , Ruihai Wu , Kunqi Xu , Yu Li , Liuyu Xiang , Hao Dong , Zhaofeng He

Multimodal LLMs have advanced vision-language tasks but still struggle with understanding video scenes. To bridge this gap, Video Scene Graph Generation (VidSGG) has emerged to capture multi-object relationships across video frames.…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Trong-Thuan Nguyen , Pha Nguyen , Jackson Cothren , Alper Yilmaz , Khoa Luu

Recent advances in Large Language Models (LLMs) have helped facilitate exciting progress for robotic planning in real, open-world environments. 3D scene graphs (3DSGs) offer a promising environment representation for grounding such…

Robotics · Computer Science 2024-11-01 Meghan Booker , Grayson Byrd , Bethany Kemp , Aurora Schmidt , Corban Rivera

We present Egocentric Action Scene Graphs (EASGs), a new representation for long-form understanding of egocentric videos. EASGs extend standard manually-annotated representations of egocentric videos, such as verb-noun action labels, by…

Computer Vision and Pattern Recognition · Computer Science 2023-12-07 Ivan Rodin , Antonino Furnari , Kyle Min , Subarna Tripathi , Giovanni Maria Farinella

Generating photorealistic images with controllable camera pose and scene contents is essential for many applications including AR/VR and simulation. Despite the fact that rapid progress has been made in 3D-aware generative models, most…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Yuanbo Yang , Yifei Yang , Hanlei Guo , Rong Xiong , Yue Wang , Yiyi Liao

Recent work has made significant progress on using implicit functions, as a continuous representation for 3D rigid object shape reconstruction. However, much less effort has been devoted to modeling general articulated objects. Compared to…

Computer Vision and Pattern Recognition · Computer Science 2021-04-16 Jiteng Mu , Weichao Qiu , Adam Kortylewski , Alan Yuille , Nuno Vasconcelos , Xiaolong Wang

We present a novel architecture aimed towards incremental construction and exploitation of a hierarchical 3D scene graph representation during semantic-aware inspection missions. Inspection planning, particularly of distributed targets in…

Despite the great success object detection and segmentation models have achieved in recognizing individual objects in images, performance on cognitive tasks such as image caption, semantic image retrieval, and visual QA is far from…

Computer Vision and Pattern Recognition · Computer Science 2024-01-25 Weilin Cong , William Wang , Wang-Chien Lee

Dynamic scene understanding is the ability of a computer system to interpret and make sense of the visual information present in a video of a real-world scene. In this thesis, we present a series of frameworks for dynamic scene…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Salman Khan

This paper investigates the integration of graph neural networks (GNNs) with Qualitative Explainable Graphs (QXGs) for scene understanding in automated driving. Scene understanding is the basis for any further reactive or proactive…

Robotics · Computer Science 2025-04-18 Nassim Belmecheri , Arnaud Gotlieb , Nadjib Lazaar , Helge Spieker

Cinemagraphs are a compelling way to convey dynamic aspects of a scene. In these media, dynamic and still elements are juxtaposed to create an artistic and narrative experience. Creating a high-quality, aesthetically pleasing cinemagraph…

Computer Vision and Pattern Recognition · Computer Science 2017-08-11 Tae-Hyun Oh , Kyungdon Joo , Neel Joshi , Baoyuan Wang , In So Kweon , Sing Bing Kang

Articulated 3D object generation is fundamental for creating realistic, functional, and interactable virtual assets which are not simply static. We introduce MeshArt, a hierarchical transformer-based approach to generate articulated 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Daoyi Gao , Yawar Siddiqui , Lei Li , Angela Dai

In crowded urban environments where traffic is dense, current technologies struggle to oversee tight navigation, but surface-level understanding allows autonomous vehicles to safely assess proximity to surrounding obstacles. 3D or 2D scene…

Computer Vision and Pattern Recognition · Computer Science 2025-06-23 Akarshani Ramanayake , Nihal Kodikara