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Related papers: Text2HOI: Text-guided 3D Motion Generation for Han…

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The ability to generate diverse 3D articulated head avatars is vital to a plethora of applications, including augmented reality, cinematography, and education. Recent work on text-guided 3D object generation has shown great promise in…

Computer Vision and Pattern Recognition · Computer Science 2023-07-12 Alexander W. Bergman , Wang Yifan , Gordon Wetzstein

Diffusion models when conditioned on text prompts, generate realistic-looking images with intricate details. But most of these pre-trained models fail to generate accurate images when it comes to human features like hands, teeth, etc. We…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Gurusha Juneja , Sukrit Kumar

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

Text-driven human motion synthesis has showcased its potential for revolutionizing motion design in the movie and game industry. Existing methods often rely on 3D motion capture data, which requires special setups, resulting in high costs…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Ruoxi Guo , Huaijin Pi , Zehong Shen , Qing Shuai , Zechen Hu , Zhumei Wang , Yajiao Dong , Ruizhen Hu , Taku Komura , Sida Peng , Xiaowei Zhou

We present an approach to learn general robot manipulation priors from 3D hand-object interaction trajectories. We build a framework to use in-the-wild videos to generate sensorimotor robot trajectories. We do so by lifting both the human…

3D generation methods have shown visually compelling results powered by diffusion image priors. However, they often fail to produce realistic geometric details, resulting in overly smooth surfaces or geometric details inaccurately baked in…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Ruihan Gao , Kangle Deng , Gengshan Yang , Wenzhen Yuan , Jun-Yan Zhu

Prevalent human-object interaction (HOI) detection approaches typically leverage large-scale visual-linguistic models to help recognize events involving humans and objects. Though promising, models trained via contrastive learning on…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Liulei Li , Wenguan Wang , Yi Yang

Egocentric interactive world models are essential for augmented reality and embodied AI, where visual generation must respond to user input with low latency, geometric consistency, and long-term stability. We study egocentric interaction…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Yuxi Wang , Wenqi Ouyang , Tianyi Wei , Yi Dong , Zhiqi Shen , Xingang Pan

Text-to-motion generation, which translates textual descriptions into human motions, faces the challenge that users often struggle to precisely convey their intended motions through text alone. To address this issue, this paper introduces…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Tao Wang , Lei Jin , Zhihua Wu , Qiaozhi He , Jiaming Chu , Yu Cheng , Junliang Xing , Jian Zhao , Shuicheng Yan , Li Wang

3D asset generation is getting massive amounts of attention, inspired by the recent success of text-guided 2D content creation. Existing text-to-3D methods use pretrained text-to-image diffusion models in an optimization problem or…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Lukas Höllein , Aljaž Božič , Norman Müller , David Novotny , Hung-Yu Tseng , Christian Richardt , Michael Zollhöfer , Matthias Nießner

Human-Object Interaction (HOI) modelling captures how humans act upon and relate to objects, typically expressed as <person, action, object> triplets. Existing approaches split into two disjoint families: HOI generation synthesises scenes…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Jiun Tian Hoe , Weipeng Hu , Xudong Jiang , Yap-Peng Tan , Chee Seng Chan

Recent years have seen an explosion of work and interest in text-to-3D shape generation. Much of the progress is driven by advances in 3D representations, large-scale pretraining and representation learning for text and image data enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Han-Hung Lee , Manolis Savva , Angel X. Chang

Reconstructing human-object interaction in 3D from a single RGB image is a challenging task and existing data driven methods do not generalize beyond the objects present in the carefully curated 3D interaction datasets. Capturing…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Xianghui Xie , Bharat Lal Bhatnagar , Jan Eric Lenssen , Gerard Pons-Moll

Recent advancements in generative models have enabled the creation of dynamic 4D content - 3D objects in motion - based on text prompts, which holds potential for applications in virtual worlds, media, and gaming. Existing methods provide…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Ohad Rahamim , Ori Malca , Dvir Samuel , Gal Chechik

We propose G-HOP, a denoising diffusion based generative prior for hand-object interactions that allows modeling both the 3D object and a human hand, conditioned on the object category. To learn a 3D spatial diffusion model that can capture…

Computer Vision and Pattern Recognition · Computer Science 2024-04-19 Yufei Ye , Abhinav Gupta , Kris Kitani , Shubham Tulsiani

Our work aims to reconstruct hand-object interactions from a single-view image, which is a fundamental but ill-posed task. Unlike methods that reconstruct from videos, multi-view images, or predefined 3D templates, single-view…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Yumeng Liu , Xiaoxiao Long , Zemin Yang , Yuan Liu , Marc Habermann , Christian Theobalt , Yuexin Ma , Wenping Wang

We present a comprehensive framework for egocentric interaction recognition using markerless 3D annotations of two hands manipulating objects. To this end, we propose a method to create a unified dataset for egocentric 3D interaction…

Computer Vision and Pattern Recognition · Computer Science 2021-08-25 Taein Kwon , Bugra Tekin , Jan Stuhmer , Federica Bogo , Marc Pollefeys

Humans inhabit a world defined by interactions -- with other humans, objects, and environments. These interactive movements not only convey our relationships with our surroundings but also demonstrate how we perceive and communicate with…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Kewei Sui , Anindita Ghosh , Inwoo Hwang , Bing Zhou , Jian Wang , Chuan Guo

In the field of human-object interaction (HOI), detection and generation are two dual tasks that have traditionally been addressed separately, hindering the development of comprehensive interaction understanding. To address this, we propose…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Panqi Yang , Haodong Jing , Nanning Zheng , Yongqiang Ma

Recent generative models can synthesize high-quality images, but they often fail to generate humans interacting with objects using their hands. This arises mostly from the model's misunderstanding of such interactions and the hardships of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Patrick Kwon , Chen Chen , Hanbyul Joo
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