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Related papers: Every Camera Effect, Every Time, All at Once: 4D G…

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Volumetric videos offer immersive 4D experiences, but remain difficult to reconstruct, store, and stream at scale. Existing Gaussian Splatting based methods achieve high-quality reconstruction but break down on long sequences, temporal…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Aashish Rai , Angela Xing , Anushka Agarwal , Xiaoyan Cong , Zekun Li , Tao Lu , Aayush Prakash , Srinath Sridhar

This work addresses the issue of motion compensation and pattern tracking in event camera data. An event camera generates asynchronous streams of events triggered independently by each of the pixels upon changes in the observed intensity.…

Computer Vision and Pattern Recognition · Computer Science 2023-03-07 Cedric Le Gentil , Ignacio Alzugaray , Teresa Vidal-Calleja

We present TraceFlow, a novel framework for high-fidelity rendering of dynamic specular scenes by addressing two key challenges: precise reflection direction estimation and physically accurate reflection modeling. To achieve this, we…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Jiachen Tao , Junyi Wu , Haoxuan Wang , Zongxin Yang , Dawen Cai , Yan Yan

Dynamic scene rendering has taken a leap forward with the rise of 4D Gaussian Splatting, but there's still one elusive challenge: how to make 3D Gaussians move through time as naturally as they would in the real world, all while keeping the…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Junli Deng , Yihao Luo

Traditional SLAM algorithms excel at camera tracking, but typically produce incomplete and low-resolution maps that are not tightly integrated with semantics prediction. Recent work integrates Gaussian Splatting (GS) into SLAM to enable…

Computer Vision and Pattern Recognition · Computer Science 2025-12-04 Mingqi Jiang , Chanho Kim , Chen Ziwen , Li Fuxin

While recent foundational video generators produce visually rich output, they still struggle with appearance drift, where objects gradually degrade or change inconsistently across frames, breaking visual coherence. We hypothesize that this…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Hyeonho Jeong , Chun-Hao Paul Huang , Jong Chul Ye , Niloy Mitra , Duygu Ceylan

Vision based robot manipulation uses cameras to capture one or more images of a scene containing the objects to be manipulated. Taking multiple images can help if any object is occluded from one viewpoint but more visible from another…

Robotics · Computer Science 2025-05-19 Abhishek Kashyap , Henrik Andreasson , Todor Stoyanov

Camera virtualization -- an emerging solution to novel view synthesis -- holds transformative potential for visual entertainment, live performances, and sports broadcasting by enabling the generation of photorealistic images from novel…

Computer Vision and Pattern Recognition · Computer Science 2026-02-18 Yunxiao Zhang , William Stone , Suryansh Kumar

The blooming of virtual reality and augmented reality (VR/AR) technologies has driven an increasing demand for the creation of high-quality, immersive, and dynamic environments. However, existing generative techniques either focus solely on…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Renjie Li , Panwang Pan , Bangbang Yang , Dejia Xu , Shijie Zhou , Xuanyang Zhang , Zeming Li , Achuta Kadambi , Zhangyang Wang , Zhengzhong Tu , Zhiwen Fan

We have recently seen tremendous progress in photo-real human modeling and rendering. Yet, efficiently rendering realistic human performance and integrating it into the rasterization pipeline remains challenging. In this paper, we present…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Yuheng Jiang , Zhehao Shen , Penghao Wang , Zhuo Su , Yu Hong , Yingliang Zhang , Jingyi Yu , Lan Xu

High-quality 4D reconstruction enables photorealistic and immersive rendering of the dynamic real world. However, unlike static scenes that can be fully captured with a single camera, high-quality dynamic scenes typically require dense…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Weihong Pan , Xiaoyu Zhang , Zhuang Zhang , Zhichao Ye , Nan Wang , Haomin Liu , Guofeng Zhang

Ray tracing algorithms, that can simulate multipath radio propagation in presence of geometric obstacles such as buildings, objects or vehicles, are becoming quite popular, due to the increasing availability of digital environment databases…

Signal Processing · Electrical Eng. & Systems 2023-06-14 Denis Bilibashi , Enrico M. Vitucci , Vittorio Degli-Esposti

Conventional geometry-based SLAM systems lack dense 3D reconstruction capabilities since their data association usually relies on feature correspondences. Additionally, learning-based SLAM systems often fall short in terms of real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Zhongche Qu , Zhi Zhang , Cong Liu , Jianhua Yin

Recent advancements in 3D Gaussian Splatting(3DGS) have significantly improved semantic scene understanding, enabling natural language queries to localize objects within a scene. However, existing methods primarily focus on embedding…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Xihan Wang , Dianyi Yang , Yu Gao , Yufeng Yue , Yi Yang , Mengyin Fu

Implicit Neural Representation (INR) has demonstrated remarkable advances in the field of image representation but demands substantial GPU resources. GaussianImage recently pioneered the use of Gaussian Splatting to mitigate this cost,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Zhaojie Zeng , Yuesong Wang , Chao Yang , Tao Guan , Lili Ju

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

4D reconstruction from casually captured monocular videos is challenging due to inherent ambiguity in reconstructing dynamic 3D geometry. To address this challenge, we introduce Robust Dynamic Gaussian Splatting (RoDyGS), a method that…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Junmyeong Lee , Hoseung Choi , Yoonwoo Jeong , Minsu Cho

Simultaneous localization and mapping (SLAM) has achieved impressive performance in static environments. However, SLAM in dynamic environments remains an open question. Many methods directly filter out dynamic objects, resulting in…

Robotics · Computer Science 2024-11-26 Haoang Li , Xiangqi Meng , Xingxing Zuo , Zhe Liu , Hesheng Wang , Daniel Cremers

3D Gaussian Splatting (3DGS) has recently gained great attention in the 3D scene representation for its high-quality real-time rendering capabilities. However, when the input comprises sparse training views, 3DGS is prone to overfitting,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Ruocheng Wu , Haolan He , Yufei Wang , Zhihao Li , Bihan Wen

3D Gaussian Splatting (3DGS) has recently emerged as a powerful representation of geometry and appearance for dense Simultaneous Localization and Mapping (SLAM). Through rapid, differentiable rasterization of 3D Gaussians, many 3DGS SLAM…

Robotics · Computer Science 2025-03-25 Xulang Liu , Ning Tan
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