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\textbf{Synthetic human dynamics} aims to generate photorealistic videos of human subjects performing expressive, intention-driven motions. However, current approaches face two core challenges: (1) \emph{geometric inconsistency} and…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Weiqi Li , Zehao Zhang , Liang Lin , Guangrun Wang

Mapping and understanding complex 3D environments is fundamental to how autonomous systems perceive and interact with the physical world, requiring both precise geometric reconstruction and rich semantic comprehension. While existing 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Naman Patel , Prashanth Krishnamurthy , Farshad Khorrami

We study the problem of synthesizing immersive 3D indoor scenes from one or more images. Our aim is to generate high-resolution images and videos from novel viewpoints, including viewpoints that extrapolate far beyond the input images while…

Computer Vision and Pattern Recognition · Computer Science 2022-12-02 Jing Yu Koh , Harsh Agrawal , Dhruv Batra , Richard Tucker , Austin Waters , Honglak Lee , Yinfei Yang , Jason Baldridge , Peter Anderson

Generative latent-variable models are emerging as promising tools in robotics and reinforcement learning. Yet, even though tasks in these domains typically involve distinct objects, most state-of-the-art generative models do not explicitly…

Machine Learning · Computer Science 2020-11-24 Martin Engelcke , Adam R. Kosiorek , Oiwi Parker Jones , Ingmar Posner

The creation of 3D human face avatars from a single unconstrained image is a fundamental task that underlies numerous real-world vision and graphics applications. Despite the significant progress made in generative models, existing methods…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Wenqing Wang , Haosen Yang , Josef Kittler , Xiatian Zhu

Recently, while text-driven human motion generation has received massive research attention, most existing text-driven motion generators are generally only designed to generate motion sequences in a blank background. While this is the case,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Haoxuan Qu , Ziyan Guo , Jun Liu

Humans can infer the three-dimensional structure of objects from two-dimensional visual inputs. Modeling this ability has been a longstanding goal for the science and engineering of visual intelligence, yet decades of computational methods…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Tyler Bonnen , Jitendra Malik , Angjoo Kanazawa

Human video synthesis aims to create lifelike characters in various environments, with wide applications in VR, storytelling, and content creation. While 2D diffusion-based methods have made significant progress, they struggle to generalize…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Liyuan Cui , Xiaogang Xu , Wenqi Dong , Zesong Yang , Hujun Bao , Zhaopeng Cui

Human activity videos involve rich, varied interactions between people and objects. In this paper we develop methods for generating such videos -- making progress toward addressing the important, open problem of video generation in complex…

Computer Vision and Pattern Recognition · Computer Science 2020-07-20 Megha Nawhal , Mengyao Zhai , Andreas Lehrmann , Leonid Sigal , Greg Mori

Human communication combines speech with expressive nonverbal cues such as hand gestures that serve manifold communicative functions. Yet, current generative gesture generation approaches are restricted to simple, repetitive beat gestures…

Human-Computer Interaction · Computer Science 2025-10-21 Hendric Voss , Stefan Kopp

Humans constantly interact with their surrounding environments. Current human-centric generative models mainly focus on synthesizing humans plausibly interacting with static scenes and objects, while the dynamic human action-reaction…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Liang Xu , Yizhou Zhou , Yichao Yan , Xin Jin , Wenhan Zhu , Fengyun Rao , Xiaokang Yang , Wenjun Zeng

Zero-shot learning on 3D point cloud data is a related underexplored problem compared to its 2D image counterpart. 3D data brings new challenges for ZSL due to the unavailability of robust pre-trained feature extraction models. To address…

Computer Vision and Pattern Recognition · Computer Science 2022-09-30 Majid Nasiri , Ali Cheraghian , Townim Faisal Chowdhury , Sahar Ahmadi , Morteza Saberi , Shafin Rahman

Scene-Graph Generation (SGG) seeks to recognize objects in an image and distill their salient pairwise relationships. Most methods depend on dataset-specific supervision to learn the variety of interactions, restricting their usefulness in…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Amartya Dutta , Kazi Sajeed Mehrab , Medha Sawhney , Abhilash Neog , Mridul Khurana , Sepideh Fatemi , Aanish Pradhan , M. Maruf , Ismini Lourentzou , Arka Daw , Anuj Karpatne

Generative vision-language models (VLMs) exhibit strong high-level image understanding but lack spatially dense alignment between vision and language modalities, as our findings indicate. Orthogonal to advancements in generative VLMs,…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Tim Lebailly , Vijay Veerabadran , Satwik Kottur , Karl Ridgeway , Michael Louis Iuzzolino

Video generation models are rapidly improving in their ability to synthesize human actions in novel contexts, holding the potential to serve as high-level planners for contextual robot control. To realize this potential, a key research…

Robotics · Computer Science 2025-12-12 James Ni , Zekai Wang , Wei Lin , Amir Bar , Yann LeCun , Trevor Darrell , Jitendra Malik , Roei Herzig

Human dance generation (HDG) aims to synthesize realistic videos from images and sequences of driving poses. Despite great success, existing methods are limited to generating videos of a single person with specific backgrounds, while the…

Computer Vision and Pattern Recognition · Computer Science 2024-01-25 Zhe Xu , Kun Wei , Xu Yang , Cheng Deng

In this study, we tackle the complex task of generating 3D human-object interactions (HOI) from textual descriptions in a zero-shot text-to-3D manner. We identify and address two key challenges: the unsatisfactory outcomes of direct…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Sisi Dai , Wenhao Li , Haowen Sun , Haibin Huang , Chongyang Ma , Hui Huang , Kai Xu , Ruizhen Hu

We present HOI-PAGE, a new approach that prioritizes part-level affordance reasoning to generate high-fidelity 4D human-object interactions (HOIs) from text prompts in a zero-shot fashion. In contrast to prior works that focus on global,…

Graphics · Computer Science 2026-05-20 Lei Li , Angela Dai

Recent advances in video diffusion models have enabled the generation of high-quality videos. However, these videos still suffer from unrealistic deformations, semantic violations, and physical inconsistencies that are largely rooted in the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Shurui Gui , Deep Anil Patel , Xiner Li , Martin Renqiang Min

High fidelity digital 3D environments have been proposed in recent years, however, it remains extremely challenging to automatically equip such environment with realistic human bodies. Existing work utilizes images, depth or semantic maps…

Computer Vision and Pattern Recognition · Computer Science 2020-11-13 Siwei Zhang , Yan Zhang , Qianli Ma , Michael J. Black , Siyu Tang