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Video tokenization procedure is critical for a wide range of video processing tasks. Most existing approaches directly transform video into fixed-grid and patch-wise tokens, which exhibit limited versatility. Spatially, uniformly allocating…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Zhenghao Chen , Zicong Chen , Lei Liu , Yiming Wu , Dong Xu

Recently, 3D Gaussian Splatting has emerged as a prominent research direction owing to its ultrarapid training speed and high-fidelity rendering capabilities. However, the unstructured and irregular nature of Gaussian point clouds poses…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Xiao Ren , Yu Liu , Ning An , Jian Cheng , Xin Qiao , He Kong

We propose GGS, a Generalizable Gaussian Splatting method for Autonomous Driving which can achieve realistic rendering under large viewpoint changes. Previous generalizable 3D gaussian splatting methods are limited to rendering novel views…

Computer Vision and Pattern Recognition · Computer Science 2024-09-05 Huasong Han , Kaixuan Zhou , Xiaoxiao Long , Yusen Wang , Chunxia Xiao

3D Gaussian Splatting (3DGS) effectively synthesizes novel views through its flexible representation, yet fails to accurately reconstruct scene geometry. While modern variants like PGSR introduce additional losses to ensure proper depth and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Zhentao Huang , Di Wu , Zhenbang He , Minglun Gong

Low-resolution (LR) multi-view capture limits the fidelity of 3D Gaussian Splatting (3DGS). 3DGS super-resolution (SR) is therefore important, yet challenging because it must recover missing high-frequency details while enforcing cross-view…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Xiang Feng , Yongbo He , Linxi Chen , Yan Yang , Chengkai Wang , Yifei Chen , Yixuan Zhong , Zhenzhong Kuang , Jiajun ding , Xufei Yin , Yanming Zhu

Free-Viewpoint Video (FVV) reconstruction enables photorealistic and interactive 3D scene visualization; however, real-time streaming is often bottlenecked by sparse-view inputs, prohibitive training costs, and bandwidth constraints. While…

Graphics · Computer Science 2026-01-27 Xinhui Liu , Can Wang , Lei Liu , Zhenghao Chen , Wei Jiang , Wei Wang , Dong Xu

Gaussian Splatting (GS), a recent technique for converting discrete points into continuous spatial representations, has shown promising results in 3D scene modeling and 2D image super-resolution. In this paper, we explore its untapped…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Hongyu Li , Chaofeng Chen , Xiaoming Li , Guangming Lu

Video representation is a long-standing problem that is crucial for various down-stream tasks, such as tracking,depth prediction,segmentation,view synthesis,and editing. However, current methods either struggle to model complex motions due…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Yang-Tian Sun , Yi-Hua Huang , Lin Ma , Xiaoyang Lyu , Yan-Pei Cao , Xiaojuan Qi

3D Gaussian Splatting is crucial for real-time novel view synthesis due to its efficiency and ability to render photorealistic images. However, building a 3D Gaussian is guided solely by photometric loss, which can result in inconsistencies…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Quan Tran , Tuan Dang

3D city generation with NeRF-based methods shows promising generation results but is computationally inefficient. Recently 3D Gaussian Splatting (3D-GS) has emerged as a highly efficient alternative for object-level 3D generation. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Haozhe Xie , Zhaoxi Chen , Fangzhou Hong , Ziwei Liu

3D Gaussian Splatting (3DGS) enables high-fidelity real-time rendering, a key requirement for immersive applications. However, the extension of 3DGS to dynamic scenes remains limitations on the substantial data volume of dense Gaussians and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Jiayu Yang , Weijian Su , Songqian Zhang , Yuqi Han , Jinli Suo , Qiang Zhang

Real-time reconstruction of deformable surgical scenes is vital for advancing robotic surgery, improving surgeon guidance, and enabling automation. Recent methods achieve dense reconstructions from da Vinci robotic surgery videos, with…

Computer Vision and Pattern Recognition · Computer Science 2026-02-23 Tianyi Song , Danail Stoyanov , Evangelos Mazomenos , Francisco Vasconcelos

3D Gaussian Splatting has demonstrated superior performance in rendering efficiency and quality, yet the generation of 3D Gaussians still remains a challenge without proper geometric priors. Existing methods have explored predicting point…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Weiqi Zhang , Junsheng Zhou , Haotian Geng , Kanle Shi , Shenkun Xu , Yi Fang , Yu-Shen Liu

Recent advancements in large generative models and real-time neural rendering using point-based techniques pave the way for a future of widespread visual data distribution through sharing synthesized 3D assets. However, while standardized…

Computer Vision and Pattern Recognition · Computer Science 2024-07-02 Chenxin Li , Hengyu Liu , Zhiwen Fan , Wuyang Li , Yifan Liu , Panwang Pan , Yixuan Yuan

3D Gaussian Splatting (3DGS) has emerged as a cutting-edge technique for real-time radiance field rendering, offering state-of-the-art performance in terms of both quality and speed. 3DGS models a scene as a collection of three-dimensional…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Milena T. Bagdasarian , Paul Knoll , Yi-Hsin Li , Florian Barthel , Anna Hilsmann , Peter Eisert , Wieland Morgenstern

3D Gaussian Splatting has achieved impressive performance in novel view synthesis with real-time rendering capabilities. However, reconstructing high-quality surfaces with fine details using 3D Gaussians remains a challenging task. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Jiepeng Wang , Yuan Liu , Peng Wang , Cheng Lin , Junhui Hou , Xin Li , Taku Komura , Wenping Wang

3D style transfer enables the creation of visually expressive 3D content, enriching the visual appearance of 3D scenes and objects. However, existing VGG- and CLIP-based methods struggle to model multi-view consistency within the model…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Yitong Yang , Xuexin Liu , Yinglin Wang , Jing Wang , Hao Dou , Changshuo Wang , Shuting He

The scarcity of large-scale 3D-text paired data poses a great challenge on open vocabulary 3D scene understanding, and hence it is popular to leverage internet-scale 2D data and transfer their open vocabulary capabilities to 3D models…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Pengfei Wang , Yuxi Wang , Shuai Li , Zhaoxiang Zhang , Zhen Lei , Lei Zhang

Diffusion-based image generators can now produce high-quality and diverse samples, but their success has yet to fully translate to 3D generation: existing diffusion methods can either generate low-resolution but 3D consistent outputs, or…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Animesh Karnewar , Niloy J. Mitra , Andrea Vedaldi , David Novotny

Recent advancements in 3D Gaussian Splatting (3DGS) have greatly influenced neural fields, as it enables high-fidelity rendering with impressive visual quality. However, 3DGS has difficulty accurately representing surfaces. In contrast,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Haofan Ren , Qingsong Yan , Ming Lu , Rongfeng Lu , Zunjie Zhu