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We propose a method to enhance 3D Gaussian Splatting (3DGS)~\cite{Kerbl2023}, addressing challenges in initialization, optimization, and density control. Gaussian Splatting is an alternative for rendering realistic images while supporting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Xingjun Wang , Lianlei Shan

Dynamic videos with small baseline motions are ubiquitous in daily life, especially on social media. However, these videos present a challenge to existing pose estimation frameworks due to ambiguous features, drift accumulation, and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-28 Yuxin Yao , Yan Zhang , Zhening Huang , Joan Lasenby

3D Gaussian Splatting (3DGS) has revolutionized neural rendering with its efficiency and quality, but like many novel view synthesis methods, it heavily depends on accurate camera poses from Structure-from-Motion (SfM) systems. Although…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Zhisheng Huang , Peng Wang , Jingdong Zhang , Yuan Liu , Xin Li , Wenping Wang

We introduce a novel geometry-guided online video view synthesis method with enhanced view and temporal consistency. Traditional approaches achieve high-quality synthesis from dense multi-view camera setups but require significant…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Hyunho Ha , Lei Xiao , Christian Richardt , Thu Nguyen-Phuoc , Changil Kim , Min H. Kim , Douglas Lanman , Numair Khan

This paper investigates the geometric consistency for monocular 3D object detection, which suffers from the ill-posed depth estimation. We first conduct a thorough analysis to reveal how existing methods fail to consistently localize…

Computer Vision and Pattern Recognition · Computer Science 2022-05-24 Qing Lian , Botao Ye , Ruijia Xu , Weilong Yao , Tong Zhang

Three-dimensional reconstruction in scenes with extreme depth variations remains challenging due to inconsistent supervisory signals between near-field and far-field regions. Existing methods fail to simultaneously address inaccurate depth…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Yu Deng , Baozhu Zhao , Junyan Su , Xiaohan Zhang , Qi Liu

We present a video generation model that accurately reproduces object motion, changes in camera viewpoint, and new content that arises over time. Existing video generation methods often fail to produce new content as a function of time…

Computer Vision and Pattern Recognition · Computer Science 2022-06-10 Tim Brooks , Janne Hellsten , Miika Aittala , Ting-Chun Wang , Timo Aila , Jaakko Lehtinen , Ming-Yu Liu , Alexei A. Efros , Tero Karras

Text-to-image generation models have achieved remarkable capabilities in synthesizing images, but often struggle to provide fine-grained control over the output. Existing guidance approaches, such as segmentation maps and depth maps,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Sangmin Jung , Utkarsh Nath , Yezhou Yang , Giulia Pedrielli , Joydeep Biswas , Amy Zhang , Hassan Ghasemzadeh , Pavan Turaga

Intrinsic image decomposition aims to estimate physically based rendering (PBR) parameters such as albedo, roughness, and metallicity from images. While recent methods achieve strong single-view predictions, applying them independently to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Alara Dirik , Stefanos Zafeiriou

Video world models aim to simulate dynamic, real-world environments, yet existing methods struggle to provide unified and precise control over camera and multi-object motion, as videos inherently capture dynamics in the projected 2D image…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Sixiao Zheng , Minghao Yin , Wenbo Hu , Xiaoyu Li , Ying Shan , Yanwei Fu

Current texture synthesis methods, which generate textures from fixed viewpoints, suffer from inconsistencies due to the lack of global context and geometric understanding. Meanwhile, recent advancements in video generation models have…

Graphics · Computer Science 2025-06-27 Donggoo Kang , Jangyeong Kim , Dasol Jeong , Junyoung Choi , Jeonga Wi , Hyunmin Lee , Joonho Gwon , Joonki Paik

Video object segmentation methods like SAM2 achieve strong performance through memory-based architectures but struggle under large viewpoint changes due to reliance on appearance features. Traditional 3D instance segmentation methods…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Yang-Che Sun , Cheng Sun , Chin-Yang Lin , Fu-En Yang , Min-Hung Chen , Yen-Yu Lin , Yu-Lun Liu

The rapid advancement of diffusion-based video generation models has led to increasingly realistic synthetic content, presenting new challenges for video forgery detection. Existing methods often struggle to capture fine-grained temporal…

Computer Vision and Pattern Recognition · Computer Science 2025-08-04 Xi Xue , Kunio Suzuki , Nabarun Goswami , Takuya Shintate

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

We tackle a new problem: generating geometrically consistent multi-view scenes from a single freehand sketch. Freehand sketches are the most geometrically impoverished input one could offer a multi-view generator. They convey scene intent…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Ahmed Bourouis , Savas Ozkan , Andrea Maracani , Yi-Zhe Song , Mete Ozay

The reconstruction of dynamic 3D scenes using 3D Gaussian Splatting has shown significant promise. A key challenge, however, remains in modeling realistic motion, as most methods fail to align the motion of Gaussians with real-world…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Junoh Lee , Junmyeong Lee , Yeon-Ji Song , Inhwan Bae , Jisu Shin , Hae-Gon Jeon , Jin-Hwa Kim

Temporal Video Grounding (TVG) aims to localize temporal moments in an untrimmed video that semantically correspond to given natural language queries. Recently, Graph Convolutional Networks (GCN) have been widely adopted in TVG to model…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Zhanjie Hu , Bolin Zhang , Jianhua Wang , Jianbo Zheng , Chenchen Yan , Takahiro Komamizu , Ichiro Ide , Jiangbo Qian

We introduce World Consistency Score (WCS), a novel unified evaluation metric for generative video models that emphasizes internal world consistency of the generated videos. WCS integrates four interpretable sub-components - object…

Computer Vision and Pattern Recognition · Computer Science 2025-08-04 Akshat Rakheja , Aarsh Ashdhir , Aryan Bhattacharjee , Vanshika Sharma

Traditional multi-view stereo (MVS) methods rely heavily on photometric and geometric consistency constraints, but newer machine learning-based MVS methods check geometric consistency across multiple source views only as a post-processing…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Vibhas K. Vats , Sripad Joshi , David J. Crandall , Md. Alimoor Reza , Soon-heung Jung

Video generation models have made significant progress in generating realistic content, enabling applications in simulation, gaming, and film making. However, current generated videos still contain visual artifacts arising from 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Duolikun Danier , Ge Gao , Steven McDonagh , Changjian Li , Hakan Bilen , Oisin Mac Aodha