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We present an approach for aggregating a sparse set of views of an object in order to compute a semi-implicit 3D representation in the form of a volumetric feature grid. Key to our approach is an object-centric canonical 3D coordinate…

Computer Vision and Pattern Recognition · Computer Science 2020-07-22 Shubham Tulsiani , Or Litany , Charles R. Qi , He Wang , Leonidas J. Guibas

Most model-free visual object tracking methods formulate the tracking task as object location estimation given by a 2D segmentation or a bounding box in each video frame. We argue that this representation is limited and instead propose to…

Computer Vision and Pattern Recognition · Computer Science 2023-04-14 Denys Rozumnyi , Jiri Matas , Marc Pollefeys , Vittorio Ferrari , Martin R. Oswald

This paper focuses on a challenging setting of simultaneously modeling geometry and appearance of hand-object interaction scenes without any object priors. We follow the trend of dynamic 3D Gaussian Splatting based methods, and address…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Hao Tian , Chenyangguang Zhang , Rui Liu , Wen Shen , Xiaolin Qin

Recent advances in 3D Gaussian Splatting have shown promising results. Existing methods typically assume static scenes and/or multiple images with prior poses. Dynamics, sparse views, and unknown poses significantly increase the problem…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Weihang Li , Weirong Chen , Shenhan Qian , Jiajie Chen , Daniel Cremers , Haoang Li

Realistic reconstruction of dynamic 4D scenes from monocular videos is essential for understanding the physical world. Despite recent progress in neural rendering, existing methods often struggle to recover accurate 3D geometry and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Haoran Zhou , Gim Hee Lee

Reconstructing and rendering 3D objects from highly sparse views is of critical importance for promoting applications of 3D vision techniques and improving user experience. However, images from sparse views only contain very limited 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-11-14 Chen Yang , Sikuang Li , Jiemin Fang , Ruofan Liang , Lingxi Xie , Xiaopeng Zhang , Wei Shen , Qi Tian

Reconstructing dynamic 3D scenes from monocular video has broad applications in AR/VR, robotics, and autonomous navigation, but often fails due to severe motion blur caused by camera and object motion. Existing methods commonly follow a…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Zhijing Wu , Longguang Wang

3D Gaussian Splatting (3DGS) has emerged as a core technique for 3D representation. Its effectiveness largely depends on precise camera poses and accurate point cloud initialization, which are often derived from pretrained Multi-View Stereo…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Chong Cheng , Zijian Wang , Sicheng Yu , Yu Hu , Nanjie Yao , Hao Wang

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

We introduce a new approach for estimating the 3D pose and the 3D shape of an object from a single image. Given a training set of view exemplars, we learn and select appearance-based discriminative parts which are mapped onto the 3D model…

Computer Vision and Pattern Recognition · Computer Science 2015-02-03 Menglong Zhu , Xiaowei Zhou , Kostas Daniilidis

We propose a novel method that tracks fast moving objects, mainly non-uniform spherical, in full 6 degrees of freedom, estimating simultaneously their 3D motion trajectory, 3D pose and object appearance changes with a time step that is a…

Computer Vision and Pattern Recognition · Computer Science 2020-10-30 Denys Rozumnyi , Jan Kotera , Filip Sroubek , Jiri Matas

3D Gaussian Splatting (3DGS) has emerged as a key rendering pipeline for digital asset creation due to its balance between efficiency and visual quality. To address the issues of unstable pose estimation and scene representation distortion…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Meijun Guo , Yongliang Shi , Caiyun Liu , Yixiao Feng , Ming Ma , Tinghai Yan , Weining Lu , Bin Liang

Region-based methods have become increasingly popular for model-based, monocular 3D tracking of texture-less objects in cluttered scenes. However, while they achieve state-of-the-art results, most methods are computationally expensive,…

Computer Vision and Pattern Recognition · Computer Science 2022-03-01 Manuel Stoiber , Martin Pfanne , Klaus H. Strobl , Rudolph Triebel , Alin Albu-Schäffer

Differentiable rendering techniques have recently shown promising results for free-viewpoint video synthesis of characters. However, such methods, either Gaussian Splatting or neural implicit rendering, typically necessitate per-subject…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Boyao Zhou , Shunyuan Zheng , Hanzhang Tu , Ruizhi Shao , Boning Liu , Shengping Zhang , Liqiang Nie , Yebin Liu

3D Gaussian Splatting (3DGS) enables real-time, photorealistic novel view synthesis, making it a highly attractive representation for model-based video tracking. However, leveraging the differentiability of the 3DGS renderer "in the wild"…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Avigail Cohen Rimon , Amir Mann , Mirela Ben Chen , Or Litany

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

Reconstructing object deformation from a single image remains a significant challenge in computer vision and graphics. Existing methods typically rely on multi-view video to recover deformation, limiting their applicability under…

Graphics · Computer Science 2025-09-29 Jinhyeok Kim , Jaehun Bang , Seunghyun Seo , Kyungdon Joo

3D reconstruction and relighting of objects made from scattering materials present a significant challenge due to the complex light transport beneath the surface. 3D Gaussian Splatting introduced high-quality novel view synthesis at…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Jan-Niklas Dihlmann , Arjun Majumdar , Andreas Engelhardt , Raphael Braun , Hendrik P. A. Lensch

Previous surface reconstruction methods either suffer from low geometric accuracy or lengthy training times when dealing with real-world complex dynamic scenes involving multi-person activities, and human-object interactions. To tackle the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Shuo Wang , Binbin Huang , Ruoyu Wang , Shenghua Gao

Camera pose refinement aims at improving the accuracy of initial pose estimation for applications in 3D computer vision. Most refinement approaches rely on 2D-3D correspondences with specific descriptors or dedicated networks, requiring…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Lulu Hao , Lipu Zhou , Zhenzhong Wei , Xu Wang