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In controllable driving-scene reconstruction and 3D scene generation, maintaining geometric fidelity while synthesizing visually plausible appearance under large viewpoint shifts is crucial. However, effective fusion of geometry-based 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 YuAn Wang , Xiaofan Li , Chi Huang , Wenhao Zhang , Hao Li , Bosheng Wang , Xun Sun , Jun Wang

Accurate and robust object pose estimation for robotics applications requires verification and refinement steps. In this work, we propose to integrate hypotheses verification with object pose refinement guided by physics simulation. This…

Computer Vision and Pattern Recognition · Computer Science 2020-05-19 Dominik Bauer , Timothy Patten , Markus Vincze

Scene generation has extensive industrial applications, demanding both high realism and precise control over geometry and appearance. Language-driven retrieval methods compose plausible scenes from a large object database, but overlook…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Zhifei Yang , Guangyao Zhai , Keyang Lu , YuYang Yin , Chao Zhang , Zhen Xiao , Jieyi Long , Nassir Navab , Yikai Wang

Egocentric human motion generation and forecasting with scene-context is crucial for enhancing AR/VR experiences, improving human-robot interaction, advancing assistive technologies, and enabling adaptive healthcare solutions by accurately…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Chaitanya Patel , Hiroki Nakamura , Yuta Kyuragi , Kazuki Kozuka , Juan Carlos Niebles , Ehsan Adeli

We consider the problem of synthesizing photorealistic, physically plausible combustion effects in in-the-wild 3D scenes. Traditional CFD and graphics pipelines can produce realistic fire effects but rely on handcrafted geometry,…

Video generation models have achieved remarkable progress in creating high-quality, photorealistic content. However, their ability to accurately simulate physical phenomena remains a critical and unresolved challenge. This paper presents…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Jing Gu , Xian Liu , Yu Zeng , Ashwin Nagarajan , Fangrui Zhu , Daniel Hong , Yue Fan , Qianqi Yan , Kaiwen Zhou , Ming-Yu Liu , Xin Eric Wang

We present a physics-based character control framework for synthesizing human-scene interactions. Recent advances adopt physics simulation to mitigate artifacts produced by data-driven kinematic approaches. However, existing physics-based…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Liang Pan , Jingbo Wang , Buzhen Huang , Junyu Zhang , Haofan Wang , Xu Tang , Yangang Wang

This paper introduces MIDI, a novel paradigm for compositional 3D scene generation from a single image. Unlike existing methods that rely on reconstruction or retrieval techniques or recent approaches that employ multi-stage…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Zehuan Huang , Yuan-Chen Guo , Xingqiao An , Yunhan Yang , Yangguang Li , Zi-Xin Zou , Ding Liang , Xihui Liu , Yan-Pei Cao , Lu Sheng

While current vision algorithms excel at many challenging tasks, it is unclear how well they understand the physical dynamics of real-world environments. Here we introduce Physion, a dataset and benchmark for rigorously evaluating the…

Urban areas, as the primary human habitat in modern civilization, accommodate a broad spectrum of social activities. With the surge of embodied intelligence, recent years have witnessed an increasing presence of physical agents in urban…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Shougao Zhang , Mengqi Zhou , Yuxi Wang , Chuanchen Luo , Rongyu Wang , Yiwei Li , Zhaoxiang Zhang , Junran Peng

Scene-consistent video generation aims to create videos that explore 3D scenes based on a camera trajectory. Previous methods rely on video generation models with external memory for consistency, or iterative 3D reconstruction and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 JiaKui Hu , Jialun Liu , Liying Yang , Xinliang Zhang , Kaiwen Li , Shuang Zeng , Yuanwei Li , Haibin Huang , Chi Zhang , Yanye Lu

Recent progress in video generation has led to impressive visual quality, yet current models still struggle to produce results that align with real-world physical principles. To this end, we propose an iterative self-refinement framework…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Yang Liu , Xilin Zhao , Peisong Wen , Siran Dai , Qingming Huang

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

3D scene reconstruction from 2D images has been a long-standing task. Instead of estimating per-frame depth maps and fusing them in 3D, recent research leverages the neural implicit surface as a unified representation for 3D reconstruction.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Xinyi Yu , Liqin Lu , Jintao Rong , Guangkai Xu , Linlin Ou

We address the issue of physical implausibility in multi-view neural reconstruction. While implicit representations have gained popularity in multi-view 3D reconstruction, previous work struggles to yield physically plausible results,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Junfeng Ni , Yixin Chen , Bohan Jing , Nan Jiang , Bin Wang , Bo Dai , Puhao Li , Yixin Zhu , Song-Chun Zhu , Siyuan Huang

Generating controllable indoor scenes is fundamental to applications in game development, architectural visualization, and embodied AI. However, existing approaches either support a limited input modalities or rely on implicit generation…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Wentang Chen , Shougao Zhang , Yiman Zhang , Tianhao Zhou , Ruihui Li

Recent advances in internet-scale video data pretraining have led to the development of text-to-video generative models that can create high-quality videos across a broad range of visual concepts, synthesize realistic motions and render…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Hritik Bansal , Zongyu Lin , Tianyi Xie , Zeshun Zong , Michal Yarom , Yonatan Bitton , Chenfanfu Jiang , Yizhou Sun , Kai-Wei Chang , Aditya Grover

Viewpoint missing of objects is common in scene reconstruction, as camera paths typically prioritize capturing the overall scene structure rather than individual objects. This makes it highly challenging to achieve high-fidelity…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Ziwei Chen , Ziling Liu , Zitong Huang , Mingqi Gao , Feng Zheng

Current text-to-image generative models struggle to accurately represent object states (e.g., "a table without a bottle," "an empty tumbler"). In this work, we first design a fully-automatic pipeline to generate high-quality synthetic data…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Tianle Chen , Chaitanya Chakka , Deepti Ghadiyaram

Recent video foundation models demonstrate impressive visual synthesis but frequently suffer from geometric inconsistencies. While existing methods attempt to inject 3D priors via architectural modifications, they often incur high…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Weijie Wang , Xiaoxuan He , Youping Gu , Yifan Yang , Zeyu Zhang , Yefei He , Yanbo Ding , Xirui Hu , Donny Y. Chen , Zhiyuan He , Yuqing Yang , Bohan Zhuang