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This paper proposes a new approach for monocular dense 3D reconstruction of a complex dynamic scene from two perspective frames. By applying superpixel over-segmentation to the image, we model a generically dynamic (hence non-rigid) scene…

Computer Vision and Pattern Recognition · Computer Science 2017-12-21 Suryansh Kumar , Yuchao Dai , Hongdong Li

Current machine learning models for vision are often highly specialized and limited to a single modality and task. In contrast, recent large language models exhibit a wide range of capabilities, hinting at a possibility for similarly…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 David Mizrahi , Roman Bachmann , Oğuzhan Fatih Kar , Teresa Yeo , Mingfei Gao , Afshin Dehghan , Amir Zamir

Recent advancements in diffusion models for 2D and 3D content creation have sparked a surge of interest in generating 4D content. However, the scarcity of 3D scene datasets constrains current methodologies to primarily object-centric…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Dejia Xu , Hanwen Liang , Neel P. Bhatt , Hezhen Hu , Hanxue Liang , Konstantinos N. Plataniotis , Zhangyang Wang

Novel view synthesis from monocular videos of dynamic scenes with unknown camera poses remains a fundamental challenge in computer vision and graphics. While recent advances in 3D representations such as Neural Radiance Fields (NeRF) and 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Mengqi Guo , Bo Xu , Yanyan Li , Gim Hee Lee

Monocular 3D reconstruction is to reconstruct the shape of object and its other information from a single RGB image. In 3D reconstruction, polygon mesh, with detailed surface information and low computational cost, is the most prevalent…

Computer Vision and Pattern Recognition · Computer Science 2023-01-31 Rongfei Zeng , Mai Su , Ruiyun Yu , Xingwei Wang

Perceiving 3D objects from monocular inputs is crucial for robotic systems, given its economy compared to multi-sensor settings. It is notably difficult as a single image can not provide any clues for predicting absolute depth values.…

Computer Vision and Pattern Recognition · Computer Science 2023-03-02 Tai Wang , Jiangmiao Pang , Dahua Lin

We present I2V3D, a novel framework for animating static images into dynamic videos with precise 3D control, leveraging the strengths of both 3D geometry guidance and advanced generative models. Our approach combines the precision of a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Zhiyuan Zhang , Dongdong Chen , Jing Liao

Recent advances in 4D scene reconstruction have significantly improved dynamic modeling across various domains. However, existing approaches remain limited under aerial conditions with single-view capture, wide spatial range, and dynamic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Hanyang Liu , Rongjun Qin

Production-level workflows for producing convincing 3D dynamic human faces have long relied on an assortment of labor-intensive tools for geometry and texture generation, motion capture and rigging, and expression synthesis. Recent neural…

Computer Vision and Pattern Recognition · Computer Science 2022-09-19 Longwen Zhang , Chuxiao Zeng , Qixuan Zhang , Hongyang Lin , Ruixiang Cao , Wei Yang , Lan Xu , Jingyi Yu

This article introduces Lester, a novel method to automatically synthetise retro-style 2D animations from videos. The method approaches the challenge mainly as an object segmentation and tracking problem. Video frames are processed with the…

Computer Vision and Pattern Recognition · Computer Science 2024-02-16 Ruben Tous

The challenge of dynamic view synthesis from dynamic monocular videos, i.e., synthesizing novel views for free viewpoints given a monocular video of a dynamic scene captured by a moving camera, mainly lies in accurately modeling the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Meng You , Junhui Hou

High-quality 4D reconstruction of human performance with complex interactions to various objects is essential in real-world scenarios, which enables numerous immersive VR/AR applications. However, recent advances still fail to provide…

Computer Vision and Pattern Recognition · Computer Science 2021-05-03 Zhuo Su , Lan Xu , Dawei Zhong , Zhong Li , Fan Deng , Shuxue Quan , Lu Fang

In this paper, we introduce \textbf{DimensionX}, a framework designed to generate photorealistic 3D and 4D scenes from just a single image with video diffusion. Our approach begins with the insight that both the spatial structure of a 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Wenqiang Sun , Shuo Chen , Fangfu Liu , Zilong Chen , Yueqi Duan , Jun Zhang , Yikai Wang

We study the problem of shape generation in 3D mesh representation from a small number of color images with or without camera poses. While many previous works learn to hallucinate the shape directly from priors, we adopt to further improve…

Computer Vision and Pattern Recognition · Computer Science 2022-04-22 Chao Wen , Yinda Zhang , Chenjie Cao , Zhuwen Li , Xiangyang Xue , Yanwei Fu

Articulated 3D object generation is fundamental for creating realistic, functional, and interactable virtual assets which are not simply static. We introduce MeshArt, a hierarchical transformer-based approach to generate articulated 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Daoyi Gao , Yawar Siddiqui , Lei Li , Angela Dai

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

Existing methods for reconstructing animatable 3D animals from videos typically rely on sparse semantic keypoints to fit parametric models. However, obtaining such keypoints is labor-intensive, and keypoint detectors trained on limited…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Shanshan Zhong , Jiawei Peng , Zehan Zheng , Zhongzhan Huang , Wufei Ma , Guofeng Zhang , Qihao Liu , Alan Yuille , Jieneng Chen

Reconstructing high-fidelity animatable human avatars from monocular videos remains challenging due to insufficient geometric information in single-view observations. While recent 3D Gaussian Splatting methods have shown promise, they…

Computer Vision and Pattern Recognition · Computer Science 2025-09-19 Jinlong Fan , Bingyu Hu , Xingguang Li , Yuxiang Yang , Jing Zhang

How can we extract complete geometric models of objects that we encounter in our daily life, without having access to commercial 3D scanners? In this paper we present an automated system for generating geometric models of objects from two…

Computer Vision and Pattern Recognition · Computer Science 2025-08-25 Floris Erich , Naoya Chiba , Abdullah Mustafa , Ryo Hanai , Noriaki Ando , Yusuke Yoshiyasu , Yukiyasu Domae

Event cameras are sensors inspired by biological systems that specialize in capturing changes in brightness. These emerging cameras offer many advantages over conventional frame-based cameras, including high dynamic range, high frame rates,…

Computer Vision and Pattern Recognition · Computer Science 2023-09-04 Haodong Chen , Vera Chung , Li Tan , Xiaoming Chen
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