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Radiance field methods, such as Neural Radiance Field or 3D Gaussian Splatting, have emerged as seminal 3D representations for synthesizing realistic novel views. For practical applications, there is ongoing research on flexible scene…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Ji Hyun Seo , Byounhyun Yoo , Gerard Jounghyun Kim

High Dynamic Range (HDR) 3D reconstruction is pivotal for professional content creation in filmmaking and virtual production. Existing methods typically rely on multi-exposure Low Dynamic Range (LDR) supervision to constrain the learning…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Kaixuan Zhang , Minxian Li , Mingwu Ren , Jiankang Deng , Xiatian Zhu

In advanced mission concepts with high levels of autonomy, spacecraft need to internally model the pose and shape of nearby orbiting objects. Recent works in neural scene representations show promising results for inferring generic…

Computer Vision and Pattern Recognition · Computer Science 2021-05-14 Anne Mergy , Gurvan Lecuyer , Dawa Derksen , Dario Izzo

Over the past two decades, research in the field of Simultaneous Localization and Mapping (SLAM) has undergone a significant evolution, highlighting its critical role in enabling autonomous exploration of unknown environments. This…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Fabio Tosi , Youmin Zhang , Ziren Gong , Erik Sandström , Stefano Mattoccia , Martin R. Oswald , Matteo Poggi

Recently, 3D Gaussian splatting (3D-GS) has gained popularity in novel-view scene synthesis. It addresses the challenges of lengthy training times and slow rendering speeds associated with Neural Radiance Fields (NeRFs). Through rapid,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-27 Sharath Girish , Kamal Gupta , Abhinav Shrivastava

Contemporary registration devices for 3D visual information, such as LIDARs and various depth cameras, capture data as 3D point clouds. In turn, such clouds are challenging to be processed due to their size and complexity. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Dominik Zimny , Joanna Waczyńska , Tomasz Trzciński , Przemysław Spurek

Recent advancements in civil infrastructure inspections underscore the need for precise three-dimensional (3D) damage visualization on digital twins, transcending traditional 2D image-based damage identifications. Compared to conventional…

Computer Vision and Pattern Recognition · Computer Science 2026-02-20 Shuo Wang , Shuo Wang , Xin Nie , Yasutaka Narazaki , Thomas Matiki , Billie F. Spencer

3D Gaussian splatting (3DGS) is a popular radiance field method, with many application-specific extensions. Most variants rely on the same core algorithm: depth-sorting of Gaussian splats then rasterizing in primitive order. This ensures…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Shakiba Kheradmand , Delio Vicini , George Kopanas , Dmitry Lagun , Kwang Moo Yi , Mark Matthews , Andrea Tagliasacchi

Efficiently synthesizing novel views from sparse inputs while maintaining accuracy remains a critical challenge in 3D reconstruction. While advanced techniques like radiance fields and 3D Gaussian Splatting achieve rendering quality and…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Chenlu Zhan , Yufei Zhang , Yu Lin , Gaoang Wang , Hongwei Wang

Novel view synthesis from unconstrained in-the-wild image collections remains a significant yet challenging task due to photometric variations and transient occluders that complicate accurate scene reconstruction. Previous methods have…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Congrong Xu , Justin Kerr , Angjoo Kanazawa

3D scene representation methods like Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have significantly advanced novel view synthesis. As these methods become prevalent, addressing their vulnerabilities becomes critical. We…

Computer Vision and Pattern Recognition · Computer Science 2025-10-03 Bo-Hsu Ke , You-Zhe Xie , Yu-Lun Liu , Wei-Chen Chiu

The recent surge in popularity of deep generative models for 3D objects has highlighted the need for more efficient training methods, particularly given the difficulties associated with training with conventional 3D representations, such as…

Computer Vision and Pattern Recognition · Computer Science 2024-08-23 Adam Kania , Artur Kasymov , Jakub Kościukiewicz , Artur Górak , Marcin Mazur , Maciej Zięba , Przemysław Spurek

Modeling reflections from 2D images is essential for photorealistic rendering and novel view synthesis. Recent approaches enhance Gaussian primitives with reflection-related material attributes to enable physically based rendering (PBR)…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Wenyuan Zhang , Jimin Tang , Weiqi Zhang , Yi Fang , Yu-Shen Liu , Zhizhong Han

Recently, 3D Gaussian Splatting (3D-GS) has achieved impressive results in novel view synthesis, demonstrating high fidelity and efficiency. However, it easily exhibits needle-like artifacts, especially when increasing the sampling rate.…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Letian Huang , Jie Guo , Jialin Dan , Ruoyu Fu , Shujie Wang , Yuanqi Li , Yanwen Guo

3D Gaussian Splatting (3DGS) has emerged as a premier method for 3D representation due to its real-time rendering and high-quality outputs, underscoring the critical need to protect the privacy of 3D assets. Traditional NeRF steganography…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Xuanyu Zhang , Jiarui Meng , Zhipei Xu , Shuzhou Yang , Yanmin Wu , Ronggang Wang , Jian Zhang

Several variants of Neural Radiance Fields (NeRFs) have significantly improved the accuracy of synthesized images and surface reconstruction of 3D scenes/objects. In all of these methods, a key characteristic is that none can train the…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Gonçalo Dias Pais , Valter Piedade , Moitreya Chatterjee , Marcus Greiff , Pedro Miraldo

Recent advances in radiance field reconstruction, such as 3D Gaussian Splatting (3DGS), have achieved high-quality novel view synthesis and fast rendering by representing scenes with compositions of Gaussian primitives. However, 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Jan Held , Renaud Vandeghen , Abdullah Hamdi , Adrien Deliege , Anthony Cioppa , Silvio Giancola , Andrea Vedaldi , Bernard Ghanem , Marc Van Droogenbroeck

3D editing plays a crucial role in many areas such as gaming and virtual reality. Traditional 3D editing methods, which rely on representations like meshes and point clouds, often fall short in realistically depicting complex scenes. On the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Yiwen Chen , Zilong Chen , Chi Zhang , Feng Wang , Xiaofeng Yang , Yikai Wang , Zhongang Cai , Lei Yang , Huaping Liu , Guosheng Lin

Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have advanced 3D reconstruction and novel view synthesis, but remain heavily dependent on accurate camera poses and dense viewpoint coverage. These requirements limit their…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Jiahui Lu , Haihong Xiao , Xueyan Zhao , Wenxiong Kang

While neural rendering has led to impressive advances in scene reconstruction and novel view synthesis, it relies heavily on accurately pre-computed camera poses. To relax this constraint, multiple efforts have been made to train Neural…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Yang Fu , Sifei Liu , Amey Kulkarni , Jan Kautz , Alexei A. Efros , Xiaolong Wang