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Experience Goal Visual Rearrangement task stands as a foundational challenge within Embodied AI, requiring an agent to construct a robust world model that accurately captures the goal state. The agent uses this world model to restore a…

Robotics · Computer Science 2024-12-18 Arjun P S , Andrew Melnik , Gora Chand Nandi

Recent developments in 3D Gaussian Splatting have made significant advances in surface reconstruction. However, scaling these methods to large-scale scenes remains challenging due to high computational demands and the complex dynamic…

Graphics · Computer Science 2025-06-24 Shihan Chen , Zhaojin Li , Zeyu Chen , Qingsong Yan , Gaoyang Shen , Ran Duan

High-fidelity 3D Gaussian Splatting methods excel at capturing fine textures but often overlook model compactness, resulting in massive splat counts, bloated memory, long training, and complex post-processing. We present Micro-Splatting:…

Graphics · Computer Science 2025-09-03 Jee Won Lee , Hansol Lim , Sooyeun Yang , Jongseong Brad Choi

Accurate 3D reconstruction of vehicles is vital for applications such as vehicle inspection, predictive maintenance, and urban planning. Existing methods like Neural Radiance Fields and Gaussian Splatting have shown impressive results but…

Computer Vision and Pattern Recognition · Computer Science 2025-07-17 Davide Di Nucci , Matteo Tomei , Guido Borghi , Luca Ciuffreda , Roberto Vezzani , Rita Cucchiara

A photorealistic and immersive human avatar experience demands capturing fine, person-specific details such as cloth and hair dynamics, subtle facial expressions, and characteristic motion patterns. Achieving this requires large,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Michael Steiner , Zhang Chen , Alexander Richard , Vasu Agrawal , Markus Steinberger , Michael Zollhöfer

This paper presents a novel system designed for 3D mapping and visual relocalization using 3D Gaussian Splatting. Our proposed method uses LiDAR and camera data to create accurate and visually plausible representations of the environment.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Peng Jiang , Gaurav Pandey , Srikanth Saripalli

In this paper, we propose a pose grammar to tackle the problem of 3D human pose estimation. Our model directly takes 2D pose as input and learns a generalized 2D-3D mapping function. The proposed model consists of a base network which…

Computer Vision and Pattern Recognition · Computer Science 2018-01-08 Haoshu Fang , Yuanlu Xu , Wenguan Wang , Xiaobai Liu , Song-Chun Zhu

Pose estimation is the task of locating keypoints for an object of interest in an image. Animal Pose estimation is more challenging than estimating human pose due to high inter and intra class variability in animals. Existing works solve…

Computer Vision and Pattern Recognition · Computer Science 2021-10-27 Gaurav Kumar Nayak , Het Shah , Anirban Chakraborty

Recent technological developments have spurred great advances in the computerized tracking of joints and other landmarks in moving animals, including humans. Such tracking promises important advances in biology and biomedicine. Modern…

Computer Vision and Pattern Recognition · Computer Science 2021-10-04 Praneet C. Bala , Jan Zimmermann , Hyun Soo Park , Benjamin Y. Hayden

Constructing a 3D scene capable of accommodating open-ended language queries, is a pivotal pursuit, particularly within the domain of robotics. Such technology facilitates robots in executing object manipulations based on human language…

Accurate 6D pose estimation of 3D objects is a fundamental task in computer vision, and current research typically predicts the 6D pose by establishing correspondences between 2D image features and 3D model features. However, these methods…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Junbo Li , Weimin Yuan , Yinuo Wang , Yue Zeng , Shihao Shu , Cai Meng , Xiangzhi Bai

Despite the advancements in quality and efficiency achieved by 3D Gaussian Splatting (3DGS) in 3D scene rendering, aliasing artifacts remain a persistent challenge. Existing approaches primarily rely on low-pass filtering to mitigate…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Zhenya Yang , Bingchen Gong , Kai Chen

Feature extraction, matching, structure from motion (SfM), and novel view synthesis (NVS) have traditionally been treated as separate problems with independent optimization objectives. We present GloSplat, a framework that performs…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Tianyu Xiong , Rui Li , Linjie Li , Jiaqi Yang

Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Marko Mihajlovic , Sergey Prokudin , Siyu Tang , Robert Maier , Federica Bogo , Tony Tung , Edmond Boyer

Automating tasks in orchards is challenging because of the large amount of variation in the environment and occlusions. One of the challenges is apple pose estimation, where key points, such as the calyx, are often occluded. Recently…

Computer Vision and Pattern Recognition · Computer Science 2025-12-24 Robert van de Ven , Trim Bresilla , Bram Nelissen , Ard Nieuwenhuizen , Eldert J. van Henten , Gert Kootstra

Despite recent progress in 3D head avatar generation, balancing identity preservation, i.e., reconstruction, with novel poses and expressions, i.e., animation, remains a challenge. Existing methods struggle to adapt Gaussians to varying…

Graphics · Computer Science 2025-07-25 SeungJun Moon , Hah Min Lew , Seungeun Lee , Ji-Su Kang , Gyeong-Moon Park

3D Gaussian Splatting (3DGS) has recently emerged as a pioneering approach in explicit scene rendering and computer graphics. Unlike traditional neural radiance field (NeRF) methods, which typically rely on implicit, coordinate-based models…

Sparse-view 3D Gaussian splatting seeks to render high-quality novel views of 3D scenes from a limited set of input images. While recent pose-free feed-forward methods leveraging pre-trained 3D priors have achieved impressive results, most…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Muyu Xu , Fangneng Zhan , Xiaoqin Zhang , Ling Shao , Shijian Lu

Creating high-quality articulated 3D models of animals is challenging either via manual creation or using 3D scanning tools. Therefore, techniques to reconstruct articulated 3D objects from 2D images are crucial and highly useful. In this…

Computer Vision and Pattern Recognition · Computer Science 2022-07-08 Chun-Han Yao , Wei-Chih Hung , Yuanzhen Li , Michael Rubinstein , Ming-Hsuan Yang , Varun Jampani

Gaussian Splatting has emerged as a prominent model for constructing 3D representations from images across diverse domains. However, the efficiency of the 3D Gaussian Splatting rendering pipeline relies on several simplifications. Notably,…

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