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Related papers: DIMO: Diverse 3D Motion Generation for Arbitrary O…

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We present DiverseMotion, a new approach for synthesizing high-quality human motions conditioned on textual descriptions while preserving motion diversity.Despite the recent significant process in text-based human motion generation,existing…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Yunhong Lou , Linchao Zhu , Yaxiong Wang , Xiaohan Wang , Yi Yang

Human motion prediction is a fundamental part of many human-robot applications. Despite the recent progress in human motion prediction, most studies simplify the problem by predicting the human motion relative to a fixed joint and/or only…

Computer Vision and Pattern Recognition · Computer Science 2022-10-04 Payam Nikdel , Mohammad Mahdavian , Mo Chen

We address the challenge of creating 3D assets for household articulated objects from a single image. Prior work on articulated object creation either requires multi-view multi-state input, or only allows coarse control over the generation…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Jiayi Liu , Denys Iliash , Angel X. Chang , Manolis Savva , Ali Mahdavi-Amiri

Generating human videos with realistic and controllable motions is a challenging task. While existing methods can generate visually compelling videos, they lack separate control over four key video elements: foreground subject, background…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Jingyun Liang , Jingkai Zhou , Shikai Li , Chenjie Cao , Lei Sun , Yichen Qian , Weihua Chen , Fan Wang

We propose a novel framework, On-Demand MOtion Generation (ODMO), for generating realistic and diverse long-term 3D human motion sequences conditioned only on action types with an additional capability of customization. ODMO shows…

Computer Vision and Pattern Recognition · Computer Science 2022-07-19 Qiujing Lu , Yipeng Zhang , Mingjian Lu , Vwani Roychowdhury

Single-image 3D reconstruction remains a fundamental challenge in computer vision due to inherent geometric ambiguities and limited viewpoint information. Recent advances in Latent Video Diffusion Models (LVDMs) offer promising 3D priors…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Yabo Chen , Chen Yang , Jiemin Fang , Xiaopeng Zhang , Lingxi Xie , Wei Shen , Wenrui Dai , Hongkai Xiong , Qi Tian

We present a novel method for generating geometrically realistic and consistent orbital videos from a single image of an object. Existing video generation works mostly rely on pixel-wise attention to enforce view consistency across frames.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Rong Wang , Ruyi Zha , Ziang Cheng , Jiayu Yang , Pulak Purkait , Hongdong Li

Generating realistic 3D hand motion from natural language is vital for VR, robotics, and human-computer interaction. Existing methods either focus on full-body motion, overlooking detailed hand gestures, or require explicit 3D object…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Ching-Lam Cheng , Bin Zhu , Shengfeng He

Diffusion models have shown great promise for image generation, beating GANs in terms of generation diversity, with comparable image quality. However, their application to 3D shapes has been limited to point or voxel representations that…

Computer Vision and Pattern Recognition · Computer Science 2022-12-16 Gimin Nam , Mariem Khlifi , Andrew Rodriguez , Alberto Tono , Linqi Zhou , Paul Guerrero

We introduce Lumina-DiMOO, an open-source foundational model for seamless multi-modal generation and understanding. Lumina-DiMOO sets itself apart from prior unified models by utilizing a fully discrete diffusion modeling to handle inputs…

Generating reasonable and high-quality human interactive motions in a given dynamic environment is crucial for understanding, modeling, transferring, and applying human behaviors to both virtual and physical robots. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Peishan Cong , Ziyi Wang , Yuexin Ma , Xiangyu Yue

We address the problem of generating diverse 3D human motions from textual descriptions. This challenging task requires joint modeling of both modalities: understanding and extracting useful human-centric information from the text, and then…

Computer Vision and Pattern Recognition · Computer Science 2022-07-25 Mathis Petrovich , Michael J. Black , Gül Varol

Information retrieval is an ever-evolving and crucial research domain. The substantial demand for high-quality human motion data especially in online acquirement has led to a surge in human motion research works. Prior works have mainly…

Computer Vision and Pattern Recognition · Computer Science 2024-03-04 Kangning Yin , Shihao Zou , Yuxuan Ge , Zheng Tian

Objects moving at high speed appear significantly blurred when captured with cameras. The blurry appearance is especially ambiguous when the object has complex shape or texture. In such cases, classical methods, or even humans, are unable…

Computer Vision and Pattern Recognition · Computer Science 2021-11-23 Denys Rozumnyi , Martin R. Oswald , Vittorio Ferrari , Jiri Matas , Marc Pollefeys

This paper presents a novel approach to generating the 3D motion of a human interacting with a target object, with a focus on solving the challenge of synthesizing long-range and diverse motions, which could not be fulfilled by existing…

Computer Vision and Pattern Recognition · Computer Science 2023-10-04 Huaijin Pi , Sida Peng , Minghui Yang , Xiaowei Zhou , Hujun Bao

Generating multi-view images based on text or single-image prompts is a critical capability for the creation of 3D content. Two fundamental questions on this topic are what data we use for training and how to ensure multi-view consistency.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Qi Zuo , Xiaodong Gu , Lingteng Qiu , Yuan Dong , Zhengyi Zhao , Weihao Yuan , Rui Peng , Siyu Zhu , Zilong Dong , Liefeng Bo , Qixing Huang

Generating future frames given a few context (or past) frames is a challenging task. It requires modeling the temporal coherence of videos and multi-modality in terms of diversity in the potential future states. Current variational…

Computer Vision and Pattern Recognition · Computer Science 2021-07-13 Gaurav Shrivastava , Abhinav Shrivastava

Animation elevates digital documents into immersive experiences, yet creating custom motion paths remains cumbersome, requiring designers to manually select presets, plot B\'ezier points, and configure timing properties. We introduce…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Mannat Khurana , Sanyam Jain , Rishav Agarwal

Recent advances in 4D generation mainly focus on generating 4D content by distilling pre-trained text or single-view image-conditioned models. It is inconvenient for them to take advantage of various off-the-shelf 3D assets with multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Yanqin Jiang , Chaohui Yu , Chenjie Cao , Fan Wang , Weiming Hu , Jin Gao

Understanding the motion of articulated mechanical assemblies from static geometry remains a core challenge in 3D perception and design automation. Prior work on everyday articulated objects such as doors and laptops typically assumes…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Mayank Patel , Rahul Jain , Asim Unmesh , Karthik Ramani