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Dense 3D reconstruction and tracking of dynamic scenes from monocular video remains an important open challenge in computer vision. Progress in this area has been constrained by the scarcity of high-quality datasets with dense, complete,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Zeren Jiang , Yushi Lan , Yihang Luo , Yufan Deng , Zihang Lai , Edgar Sucar , Christian Rupprecht , Iro Laina , Diane Larlus , Chuanxia Zheng , Andrea Vedaldi

Reconstructing dynamic 3D scenes from 2D images and generating diverse views over time is challenging due to scene complexity and temporal dynamics. Despite advancements in neural implicit models, limitations persist: (i) Inadequate Scene…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Zeyu Yang , Hongye Yang , Zijie Pan , Li Zhang

Super-resolution reconstruction techniques entail the utilization of software algorithms to transform one or more sets of low-resolution images captured from the same scene into high-resolution images. In recent years, considerable…

Computer Vision and Pattern Recognition · Computer Science 2024-08-02 Hao Yan , Zixiang Wang , Zhengjia Xu , Zhuoyue Wang , Zhizhong Wu , Ranran Lyu

3D rendering of dynamic face captures is a challenging problem, and it demands improvements on several fronts$\unicode{x2014}$photorealism, efficiency, compatibility, and configurability. We present a novel representation that enables…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Safa C. Medin , Gengyan Li , Ruofei Du , Stephan Garbin , Philip Davidson , Gregory W. Wornell , Thabo Beeler , Abhimitra Meka

In this paper, we propose a novel framework for solving high-definition video inverse problems using latent image diffusion models. Building on recent advancements in spatio-temporal optimization for video inverse problems using image…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Taesung Kwon , Jong Chul Ye

We present Tensor4D, an efficient yet effective approach to dynamic scene modeling. The key of our solution is an efficient 4D tensor decomposition method so that the dynamic scene can be directly represented as a 4D spatio-temporal tensor.…

Computer Vision and Pattern Recognition · Computer Science 2023-04-14 Ruizhi Shao , Zerong Zheng , Hanzhang Tu , Boning Liu , Hongwen Zhang , Yebin Liu

Human performance capture is a highly important computer vision problem with many applications in movie production and virtual/augmented reality. Many previous performance capture approaches either required expensive multi-view setups or…

Computer Vision and Pattern Recognition · Computer Science 2021-11-23 Marc Habermann , Weipeng Xu , Michael Zollhoefer , Gerard Pons-Moll , Christian Theobalt

Advancements in 3D scene reconstruction have transformed 2D images from the real world into 3D models, producing realistic 3D results from hundreds of input photos. Despite great success in dense-view reconstruction scenarios, rendering a…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Fangfu Liu , Wenqiang Sun , Hanyang Wang , Yikai Wang , Haowen Sun , Junliang Ye , Jun Zhang , Yueqi Duan

In this work, we propose a method to address the challenge of rendering a 3D human from a single image in a free-view manner. Some existing approaches could achieve this by using generalizable pixel-aligned implicit fields to reconstruct a…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Xiangjun Gao , Xiaoyu Li , Chaopeng Zhang , Qi Zhang , Yanpei Cao , Ying Shan , Long Quan

While the presentation of photo-realistic appearance plays a major role in immersion in an augmented virtuality environment, displaying the photo-realistic appearance of real objects remains a challenging problem. Recent developments in…

Human-Computer Interaction · Computer Science 2022-10-25 Yuichi Hiroi , Yuta Itoh , Jun Rekimoto

Widespread RGB-Depth (RGB-D) sensors and advanced 3D reconstruction technologies facilitate the capture of indoor spaces, improving the fields of augmented reality (AR), virtual reality (VR), and extended reality (XR). Nevertheless, current…

Robotics · Computer Science 2026-04-22 Seok Joon Kim , Dinh Duc Cao , Federica Spinola , Se Jin Lee , Kyu Sung Cho

Facial geometry and appearance capture have demonstrated tremendous success in 3D scanning real humans in studios. Recent works propose to democratize this technique while keeping the results high quality. However, they are still…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Yuxuan Han , Junfeng Lyu , Feng Xu

Creating plausible virtual actors from images of real actors remains one of the key challenges in computer vision and computer graphics. Marker-less human motion estimation and shape modeling from images in the wild bring this challenge to…

Computer Vision and Pattern Recognition · Computer Science 2020-01-22 Thiago L. Gomes , Renato Martins , João Ferreira , Erickson R. Nascimento

Event cameras are bio-inspired sensors that offer several advantages, such as low latency, high-speed and high dynamic range, to tackle challenging scenarios in computer vision. This paper presents a solution to the problem of 3D…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Yi Zhou , Guillermo Gallego , Henri Rebecq , Laurent Kneip , Hongdong Li , Davide Scaramuzza

This paper tackles the challenge of recovering 4D dynamic scenes from videos captured by as few as four portable cameras. Learning to model scene dynamics for temporally consistent novel-view rendering is a foundational task in computer…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Junsheng Zhou , Zhifan Yang , Liang Han , Wenyuan Zhang , Kanle Shi , Shenkun Xu , Yu-Shen Liu

Capturing and faithfully rendering photo-realistic humans from novel views is a fundamental problem for AR/VR applications. While prior work has shown impressive performance capture results in laboratory settings, it is non-trivial to…

Computer Vision and Pattern Recognition · Computer Science 2022-08-03 Phong Nguyen-Ha , Nikolaos Sarafianos , Christoph Lassner , Janne Heikkila , Tony Tung

Recovering 4D from monocular video, which jointly estimates dynamic geometry and camera poses, is an inevitably challenging problem. While recent pointmap-based 3D reconstruction methods (e.g., DUSt3R) have made great progress in…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Shizun Wang , Zhenxiang Jiang , Xingyi Yang , Xinchao Wang

We present a novel method to learn temporally consistent 3D reconstruction of clothed people from a monocular video. Recent methods for 3D human reconstruction from monocular video using volumetric, implicit or parametric human shape…

Computer Vision and Pattern Recognition · Computer Science 2021-04-20 Akin Caliskan , Armin Mustafa , Adrian Hilton

Recovering the shape and appearance of real-world objects from natural 2D images is a long-standing and challenging inverse rendering problem. In this paper, we introduce a novel hybrid differentiable rendering method to efficiently…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Xiangyang Zhu , Yiling Pan , Bailin Deng , Bin Wang

4D Gaussian Splatting (4DGS) has recently gained considerable attention as a method for reconstructing dynamic scenes. Despite achieving superior quality, 4DGS typically requires substantial storage and suffers from slow rendering speed. In…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Yuheng Yuan , Qiuhong Shen , Xingyi Yang , Xinchao Wang