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Related papers: CRAG: Can 3D Generative Models Help 3D Assembly?

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Robots operating in unstructured environments often require accurate and consistent object-level representations. This typically requires segmenting individual objects from the robot's surroundings. While recent large models such as Segment…

Robotics · Computer Science 2025-04-07 Haozhan Tang , Tianyi Zhang , Oliver Kroemer , Matthew Johnson-Roberson , Weiming Zhi

The rapid development of large language models has led to the widespread adoption of Retrieval-Augmented Generation (RAG), which integrates external knowledge to alleviate knowledge bottlenecks and mitigate hallucinations. However, the…

Computation and Language · Computer Science 2024-10-10 Ruotong Pan , Boxi Cao , Hongyu Lin , Xianpei Han , Jia Zheng , Sirui Wang , Xunliang Cai , Le Sun

Retrieval-Augmented Generation (RAG) systems enhance text generation by incorporating external knowledge but often struggle when retrieving context across different text modalities due to semantic gaps. We introduce a generalized…

Machine Learning · Computer Science 2024-11-01 Arihan Yadav , Alan McMillan

While recent advancements have shown remarkable progress in general 3D shape generation models, the challenge of leveraging these approaches to automatically generate wearable 3D assets remains unexplored. To this end, we present BAG, a…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Zhongjin Luo , Yang Li , Mingrui Zhang , Senbo Wang , Han Yan , Xibin Song , Taizhang Shang , Wei Mao , Hongdong Li , Xiaoguang Han , Pan Ji

We propose a new procedure to guide training of a data-driven shape generative model using a structure-aware loss function. Complex 3D shapes often can be summarized using a coarsely defined structure which is consistent and robust across…

Computer Vision and Pattern Recognition · Computer Science 2018-08-07 Elena Balashova , Vivek Singh , Jiangping Wang , Brian Teixeira , Terrence Chen , Thomas Funkhouser

Reconstructing multi-human body mesh from a single monocular image is an important but challenging computer vision problem. In addition to the individual body mesh models, we need to estimate relative 3D positions among subjects to generate…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Chenyan Wu , Yandong Li , Xianfeng Tang , James Wang

Advances in CAD and CAM have enabled engineers and design teams to digitally design parts with unprecedented ease. Software solutions now come with a range of modules for optimizing designs for performance requirements, generating…

Computational Engineering, Finance, and Science · Computer Science 2024-09-06 Hongrui Chen , Aditya Joglekar , Zack Rubinstein , Bradley Schmerl , Gary Fedder , Jan de Nijs , David Garlan , Stephen Smith , Levent Burak Kara

Retrieval Augmented Generation (RAG) systems, despite their growing popularity for enhancing model response reliability, often struggle with trustworthiness and explainability. In this work, we present a novel, holistic, model-agnostic,…

Information Retrieval · Computer Science 2025-09-10 Viju Sudhi , Sinchana Ramakanth Bhat , Max Rudat , Roman Teucher , Nicolas Flores-Herr

Estimating the 3D shape of an object using a single image is a difficult problem. Modern approaches achieve good results for general objects, based on real photographs, but worse results on less expressive representations such as historic…

Computer Vision and Pattern Recognition · Computer Science 2024-02-14 Thomas Pöllabauer , Julius Kühn , Jiayi Li , Arjan Kuijper

Despite recent progress, text-to-image models still struggle to generate semantically diverse and compositionally accurate multi-person interaction scenes, often collapsing to repetitive layouts, stereotypical poses, and poorly grounded…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Wenxuan Peng , Bharath Hariharan , Hadar Averbuch-Elor

Inspired by traditional handmade crafts, where a person improvises assemblies based on the available objects, we formally introduce the Craft Assembly Task. It is a robotic assembly task that involves building an accurate representation of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Vitor Hideyo Isume , Takuya Kiyokawa , Natsuki Yamanobe , Yukiyasu Domae , Weiwei Wan , Kensuke Harada

To endow machines with the ability to perceive the real-world in a three dimensional representation as we do as humans is a fundamental and long-standing topic in Artificial Intelligence. Given different types of visual inputs such as…

Computer Vision and Pattern Recognition · Computer Science 2020-10-20 Bo Yang

The demands on robotic manipulation skills to perform challenging tasks have drastically increased in recent times. To perform these tasks with dexterity, robots require perception tools to understand the scene and extract useful…

Robotics · Computer Science 2023-12-06 K. Samarawickrama , G. Sharma , A. Angleraud , R. Pieters

We introduce AutoPartGen, a model that generates objects composed of 3D parts in an autoregressive manner. This model can take as input an image of an object, 2D masks of the object's parts, or an existing 3D object, and generate a…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Minghao Chen , Jianyuan Wang , Roman Shapovalov , Tom Monnier , Hyunyoung Jung , Dilin Wang , Rakesh Ranjan , Iro Laina , Andrea Vedaldi

Recent breakthroughs in text-guided image generation have significantly advanced the field of 3D generation. While generating a single high-quality 3D object is now feasible, generating multiple objects with reasonable interactions within a…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Chongjian Ge , Chenfeng Xu , Yuanfeng Ji , Chensheng Peng , Masayoshi Tomizuka , Ping Luo , Mingyu Ding , Varun Jampani , Wei Zhan

Recent generative models can synthesize "views" of artificial images that mimic real-world variations, such as changes in color or pose, simply by learning from unlabeled image collections. Here, we investigate whether such views can be…

Computer Vision and Pattern Recognition · Computer Science 2021-04-30 Lucy Chai , Jun-Yan Zhu , Eli Shechtman , Phillip Isola , Richard Zhang

We present a deep generative scene modeling technique for indoor environments. Our goal is to train a generative model using a feed-forward neural network that maps a prior distribution (e.g., a normal distribution) to the distribution of…

Computer Vision and Pattern Recognition · Computer Science 2018-08-08 Zaiwei Zhang , Zhenpei Yang , Chongyang Ma , Linjie Luo , Alexander Huth , Etienne Vouga , Qixing Huang

3D objects (artefacts) are made to fulfill functions. Designing an object often starts with defining a list of functionalities that it should provide, also known as functional requirements. Today, the design of 3D object models is still a…

Artificial Intelligence · Computer Science 2018-10-18 Mihai Andries , Atabak Dehban , José Santos-Victor

The development of a generic and effective force model for semi-automatic or manual virtual assembly with haptic support is not a trivial task, especially when the assembly constraints involve complex features of arbitrary shape. The…

Human-Computer Interaction · Computer Science 2017-12-05 Morad Behandish , Horea T. Ilies

Retrieval-Augmented Generation (RAG) technology has been widely applied in recent years. However, despite the emergence of various RAG frameworks, a single RAG framework still cannot adapt well to a broad range of downstream tasks.…

Artificial Intelligence · Computer Science 2025-08-20 Yifei Chen , Guanting Dong , Yutao Zhu , Zhicheng Dou