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Neural Radiance Fields (NeRF) enable 3D scene reconstruction from 2D images and camera poses for Novel View Synthesis (NVS). Although NeRF can produce photorealistic results, it often suffers from overfitting to training views, leading to…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Fusang Wang , Arnaud Louys , Nathan Piasco , Moussab Bennehar , Luis Roldão , Dzmitry Tsishkou

3D Gaussian Splatting has recently achieved notable success in novel view synthesis for dynamic scenes and geometry reconstruction in static scenes. Building on these advancements, early methods have been developed for dynamic surface…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Decai Chen , Brianne Oberson , Ingo Feldmann , Oliver Schreer , Anna Hilsmann , Peter Eisert

In recent years, a growing body of research has focused on the problem of person re-identification (re-id). The re-id techniques attempt to match the images of pedestrians from disjoint non-overlapping camera views. A major challenge of…

Computer Vision and Pattern Recognition · Computer Science 2018-04-02 Zhanxiang Feng , Jianhuang Lai , Xiaohua Xie

Novel view synthesis requires strong 3D geometric consistency and the ability to generate visually coherent images across diverse viewpoints. While recent camera-controlled video diffusion models show promising results, they often suffer…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Minjun Kang , Inkyu Shin , Taeyeop Lee , Myungchul Kim , In So Kweon , Kuk-Jin Yoon

Image-to-point cloud cross-modal Visual Place Recognition (VPR) is a challenging task where the query is an RGB image, and the database samples are LiDAR point clouds. Compared to single-modal VPR, this approach benefits from the widespread…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 Jianyi Peng , Fan Lu , Bin Li , Yuan Huang , Sanqing Qu , Guang Chen

Class-agnostic 3D instance segmentation tackles the challenging task of segmenting all object instances, including previously unseen ones, without semantic class reliance. Current methods struggle with generalization due to the scarce…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Shengchao Zhou , Jiehong Lin , Jiahui Liu , Shizhen Zhao , Chirui Chang , Xiaojuan Qi

This paper presents a new method to synthesize an image from arbitrary views and times given a collection of images of a dynamic scene. A key challenge for the novel view synthesis arises from dynamic scene reconstruction where epipolar…

Computer Vision and Pattern Recognition · Computer Science 2020-04-06 Jae Shin Yoon , Kihwan Kim , Orazio Gallo , Hyun Soo Park , Jan Kautz

Recent advancements in 3D robotic manipulation have improved grasping of everyday objects, but transparent and specular materials remain challenging due to depth sensing limitations. While several 3D reconstruction and depth completion…

Robotics · Computer Science 2025-06-23 Mingxu Zhang , Xiaoqi Li , Jiahui Xu , Kaichen Zhou , Hojin Bae , Yan Shen , Chuyan Xiong , Hao Dong

Recent advancements in 3D Gaussian Splatting (3D-GS) have established new benchmarks for rendering quality and efficiency in 3D reconstruction. However, 3D-GS faces critical limitations when generating novel views that significantly deviate…

Graphics · Computer Science 2025-03-05 Yifei Gao , Kerui Ren , Jie Ou , Lei Wang , Jiaji Wu , Jun Cheng

Accurate and efficient 3D reconstruction of trees is crucial for forest resource assessments and management. Close-Range Photogrammetry (CRP) is commonly used for reconstructing forest scenes but faces challenges like low efficiency and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Guoji Tian , Chongcheng Chen , Hongyu Huang

3D Visual Grounding (3DVG) aims to locate objects in 3D scenes based on text prompts, which is essential for applications such as robotics. However, existing 3DVG methods encounter two main challenges: first, they struggle to handle the…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Liwei Liao , Xufeng Li , Xiaoyun Zheng , Boning Liu , Feng Gao , Ronggang Wang

View synthesis aims to produce unseen views from a set of views captured by two or more cameras at different positions. This task is non-trivial since it is hard to conduct pixel-level matching among different views. To address this issue,…

Computer Vision and Pattern Recognition · Computer Science 2021-01-27 Zhuoman Liu , Wei Jia , Ming Yang , Peiyao Luo , Yong Guo , Mingkui Tan

Novel view synthesis (NVS) seeks to render photorealistic, 3D-consistent images of a scene from unseen camera poses given only a sparse set of posed views. Existing deterministic networks render observed regions quickly but blur unobserved…

Computer Vision and Pattern Recognition · Computer Science 2025-12-24 Thanh-Tung Le , Tuan Pham , Tung Nguyen , Deying Kong , Xiaohui Xie , Stephan Mandt

Current methods for 3D scene reconstruction from sparse posed images employ intermediate 3D representations such as neural fields, voxel grids, or 3D Gaussians, to achieve multi-view consistent scene appearance and geometry. In this paper…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Vitor Guizilini , Muhammad Zubair Irshad , Dian Chen , Greg Shakhnarovich , Rares Ambrus

Dynamic Neural Radiance Fields (NeRFs) achieve remarkable visual quality when synthesizing novel views of time-evolving 3D scenes. However, the common reliance on backward deformation fields makes reanimation of the captured object poses…

Computer Vision and Pattern Recognition · Computer Science 2024-02-12 Lukas Uzolas , Elmar Eisemann , Petr Kellnhofer

Differentiable volumetric rendering is a powerful paradigm for 3D reconstruction and novel view synthesis. However, standard volume rendering approaches struggle with degenerate geometries in the case of limited viewpoint diversity, a…

Computer Vision and Pattern Recognition · Computer Science 2023-04-07 Vitor Guizilini , Igor Vasiljevic , Jiading Fang , Rares Ambrus , Sergey Zakharov , Vincent Sitzmann , Adrien Gaidon

We leverage repetitive elements in 3D scenes to improve novel view synthesis. Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have greatly improved novel view synthesis but renderings of unseen and occluded parts remain…

Current point-based approaches encounter limitations in scalability and rendering quality when using large 3D point cloud maps because using them directly for novel view synthesis (NVS) leads to degraded visualizations. We identify the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Mohammad Altillawi , Fengyi Shen , Liudi Yang , Sai Manoj Prakhya , Ziyuan Liu

We propose a 3D novel sparse-view synthesis framework for unconstrained real-world scenarios that contain distractors. Unlike existing methods that primarily perform novel-view synthesis from a sparse set of constrained images without…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Wongi Park , Jordan A. James , Myeongseok Nam , Minjae Lee , Soomok Lee , Sang-Hyun Lee , William J. Beksi

Single-view 3D reconstruction is currently approached from two dominant perspectives: reconstruction of scenes with limited diversity using 3D data supervision or reconstruction of diverse singular objects using large image priors. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Andreea Ardelean , Mert Özer , Bernhard Egger