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Reconstructing dynamic scenes from video sequences is a highly promising task in the multimedia domain. While previous methods have made progress, they often struggle with slow rendering and managing temporal complexities such as…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Jinbo Yan , Rui Peng , Luyang Tang , Ronggang Wang

Implicit Neural Representation for Videos (NeRV) has introduced a novel paradigm for video representation and compression, outperforming traditional codecs. As model size grows, however, slow encoding and decoding speed and high memory…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Inseo Lee , Youngyoon Choi , Joonseok Lee

We introduce Mono4DGS-HDR, the first system for reconstructing renderable 4D high dynamic range (HDR) scenes from unposed monocular low dynamic range (LDR) videos captured with alternating exposures. To tackle such a challenging problem, we…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Jinfeng Liu , Lingtong Kong , Mi Zhou , Jinwen Chen , Dan Xu

Remarkable advances in recent 2D image and 3D shape generation have induced a significant focus on dynamic 4D content generation. However, previous 4D generation methods commonly struggle to maintain spatial-temporal consistency and adapt…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Mengmeng Liu , Jiuming Liu , Yunpeng Zhang , Jiangtao Li , Michael Ying Yang , Francesco Nex , Hao Cheng

Recent 4D Gaussian Splatting (4DGS) methods achieve impressive dynamic scene reconstruction but often rely on piecewise linear velocity approximations and short temporal windows. This disjointed modeling leads to severe temporal…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Suwoong Yeom , Joonsik Nam , Seunggyu Choi , Lucas Yunkyu Lee , Sangmin Kim , Jaesik Park , Joonsoo Kim , Kugjin Yun , Kyeongbo Kong , Sukju Kang

The task of capturing and rendering 3D dynamic scenes from 2D images has become increasingly popular in recent years. However, most conventional cameras are bandwidth-limited to 30-60 FPS, restricting these methods to static or slowly…

Computer Vision and Pattern Recognition · Computer Science 2026-04-30 David Novikov , Eilon Vaknin , Narek Tumanyan , Mark Sheinin

While dynamic novel view synthesis from 2D videos has seen progress, achieving efficient reconstruction and rendering of dynamic scenes remains a challenging task. In this paper, we introduce Disentangled 4D Gaussian Splatting…

Graphics · Computer Science 2025-10-31 Hao Feng , Hao Sun , Wei Xie , Zhi Zuo , Zhengzhe Liu

3D Gaussian splatting (3DGS) has demonstrated exceptional performance in image-based 3D reconstruction and real-time rendering. However, regions with complex textures require numerous Gaussians to capture significant color variations…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Binxiao Huang , Zhihao Li , Shiyong Liu , Xiao Tang , Jiajun Tang , Jiaqi Lin , Yuxin Cheng , Zhenyu Chen , Xiaofei Wu , Ngai Wong

Recent 4D reconstruction methods have yielded impressive results but rely on sharp videos as supervision. However, motion blur often occurs in videos due to camera shake and object movement, while existing methods render blurry results when…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Renlong Wu , Zhilu Zhang , Mingyang Chen , Zifei Yan , Wangmeng Zuo

The online reconstruction of dynamic scenes from multi-view streaming videos faces significant challenges in training, rendering and storage efficiency. Harnessing superior learning speed and real-time rendering capabilities, 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Qiankun Gao , Jiarui Meng , Chengxiang Wen , Jie Chen , Jian Zhang

4D head capture aims to generate dynamic topological meshes and corresponding texture maps from videos, which is widely utilized in movies and games for its ability to simulate facial muscle movements and recover dynamic textures in…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Xuanchen Li , Yuhao Cheng , Xingyu Ren , Haozhe Jia , Di Xu , Wenhan Zhu , Yichao Yan

Synthesizing novel views from monocular videos of dynamic scenes remains a challenging problem. Scene-specific methods that optimize 4D representations with explicit motion priors often break down in highly dynamic regions where multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Thomas Tanay , Mohammed Brahimi , Michal Nazarczuk , Qingwen Zhang , Sibi Catley-Chandar , Arthur Moreau , Zhensong Zhang , Eduardo Pérez-Pellitero

3D Gaussian Splatting has shown fast and high-quality rendering results in static scenes by leveraging dense 3D prior and explicit representations. Unfortunately, the benefits of the prior and representation do not involve novel view…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Junoh Lee , Chang-Yeon Won , Hyunjun Jung , Inhwan Bae , Hae-Gon Jeon

Recent advancements in generative video codec (GVC) typically encode video into a 2D latent grid and employ high-capacity generative decoders for reconstruction. However, this paradigm still leaves two key challenges in fully exploiting…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Zihan Zheng , Zhaoyang Jia , Naifu Xue , Jiahao Li , Bin Li , Zongyu Guo , Xiaoyi Zhang , Zhenghao Chen , Houqiang Li , Yan Lu

We present MVSGaussian, a new generalizable 3D Gaussian representation approach derived from Multi-View Stereo (MVS) that can efficiently reconstruct unseen scenes. Specifically, 1) we leverage MVS to encode geometry-aware Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Tianqi Liu , Guangcong Wang , Shoukang Hu , Liao Shen , Xinyi Ye , Yuhang Zang , Zhiguo Cao , Wei Li , Ziwei Liu

Novel view synthesis of dynamic scenes has been an intriguing yet challenging problem. Despite recent advancements, simultaneously achieving high-resolution photorealistic results, real-time rendering, and compact storage remains a…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Zhan Li , Zhang Chen , Zhong Li , Yi Xu

To achieve realistic immersion in landscape images, fluids such as water and clouds need to move within the image while revealing new scenes from various camera perspectives. Recently, a field called dynamic scene video has emerged, which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 In-Hwan Jin , Haesoo Choo , Seong-Hun Jeong , Heemoon Park , Junghwan Kim , Oh-joon Kwon , Kyeongbo Kong

Image view synthesis has seen great success in reconstructing photorealistic visuals, thanks to deep learning and various novel representations. The next key step in immersive virtual experiences is view synthesis of dynamic scenes.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Kai-En Lin , Guowei Yang , Lei Xiao , Feng Liu , Ravi Ramamoorthi

Video super-resolution (VSR) approaches have shown impressive temporal consistency in upsampled videos. However, these approaches tend to generate blurrier results than their image counterparts as they are limited in their generative…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Yiran Xu , Taesung Park , Richard Zhang , Yang Zhou , Eli Shechtman , Feng Liu , Jia-Bin Huang , Difan Liu

Efficient representations of multivariate functions are critical for the design of state-of-the-art methods of data restoration and image reconstruction. In this work, we consider the representation of spatio-temporal data such as temporal…

Functional Analysis · Mathematics 2023-09-20 Tatiana A. Bubba , Glenn Easley , Tommi Heikkilä , Demetrio Labate , Jose P. Rodriguez Ayllon