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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

Generating immersive 3D scenes from texts is a core task in computer vision, crucial for applications in virtual reality and game development. Despite the promise of leveraging 2D diffusion priors, existing methods suffer from spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Jisheng Chu , Wenrui Li , Rui Zhao , Wangmeng Zuo , Shifeng Chen , Xiaopeng Fan

3D Gaussian Splatting shows great potential in reconstructing photo-realistic 3D scenes. However, these methods typically bake illumination into their representations, limiting their use for physically-based rendering and scene editing.…

Graphics · Computer Science 2025-04-03 Zirui Wu , Jianteng Chen , Laijian Li , Shaoteng Wu , Zhikai Zhu , Kang Xu , Martin R. Oswald , Jie Song

2D cameras are often used in interactive systems. Other systems like gaming consoles provide more powerful 3D cameras for short range depth sensing. Overall, these cameras are not reliable in large, complex environments. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Mohamed Benkedadra , Matei Mancas , Sidi Ahmed Mahmoudi

Capturing and reconstructing a human actor's motion is important for filmmaking and gaming. Currently, motion capture systems with static cameras are used for pixel-level high-fidelity reconstructions. Such setups are costly, require…

Robotics · Computer Science 2023-08-02 Qingyuan Jiang , Volkan Isler

3D rendering of dynamic face captures is a challenging problem, and it demands improvements on several fronts$\unicode{x2014}$photorealism, efficiency, compatibility, and configurability. We present a novel representation that enables…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Safa C. Medin , Gengyan Li , Ruofei Du , Stephan Garbin , Philip Davidson , Gregory W. Wornell , Thabo Beeler , Abhimitra Meka

Currently, there are no learning-free or neural techniques for real-time recalibration of infrared multi-camera systems. In this paper, we address the challenge of real-time, highly-accurate calibration of multi-camera infrared systems, a…

Computer Vision and Pattern Recognition · Computer Science 2024-10-21 Benyamin Mehmandar , Reza Talakoob , Charalambos Poullis

The colorful appearance of a physical painting is determined by the distribution of paint pigments across the canvas, which we model as a per-pixel mixture of a small number of pigments with multispectral absorption and scattering…

Graphics · Computer Science 2018-07-23 Jianchao Tan , Stephen DiVerdi , Jingwan Lu , Yotam Gingold

Existing image inpainting methods often produce artifacts when dealing with large holes in real applications. To address this challenge, we propose an iterative inpainting method with a feedback mechanism. Specifically, we introduce a deep…

Computer Vision and Pattern Recognition · Computer Science 2020-07-15 Yu Zeng , Zhe Lin , Jimei Yang , Jianming Zhang , Eli Shechtman , Huchuan Lu

Neural rendering provides a fundamentally new way to render photorealistic images. Similar to traditional light-baking methods, neural rendering utilizes neural networks to bake representations of scenes, materials, and lights into latent…

Graphics · Computer Science 2024-05-30 Ziyang Zhang , Edgar Simo-Serra

Inverse rendering aims to reconstruct geometry and reflectance of objects from images. Despite recent progress, existing methods often produces inaccurate reconstructions that are sensitive to ambient illumination conditions. Here we…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Hoon-Gyu Chung , Jinnyeong Kim , Hyunwoo Kang , Seung-Hwan Baek

Neural rendering is a new image and video generation method based on deep learning. It combines the deep learning model with the physical knowledge of computer graphics, to obtain a controllable and realistic scene model, and realize the…

Graphics · Computer Science 2024-02-02 Xinkai Yan , Jieting Xu , Yuchi Huo , Hujun Bao

We present a new point-based approach for modeling the appearance of real scenes. The approach uses a raw point cloud as the geometric representation of a scene, and augments each point with a learnable neural descriptor that encodes local…

Computer Vision and Pattern Recognition · Computer Science 2020-04-07 Kara-Ali Aliev , Artem Sevastopolsky , Maria Kolos , Dmitry Ulyanov , Victor Lempitsky

This paper introduces a general approach to dynamic scene reconstruction from multiple moving cameras without prior knowledge or limiting constraints on the scene structure, appearance, or illumination. Existing techniques for dynamic scene…

Computer Vision and Pattern Recognition · Computer Science 2015-10-01 Armin Mustafa , Hansung Kim , Jean-Yves Guillemaut , Adrian Hilton

We present a method for relighting 3D reconstructions of large room-scale environments. Existing solutions for 3D scene relighting often require solving under-determined or ill-conditioned inverse rendering problems, and are as such unable…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Xiaoyan Xing , Philipp Henzler , Junhwa Hur , Runze Li , Jonathan T. Barron , Pratul P. Srinivasan , Dor Verbin

In this work, we present an effective multi-view approach to closed-loop end-to-end learning of precise manipulation tasks that are 3D in nature. Our method learns to accomplish these tasks using multiple statically placed but uncalibrated…

Robotics · Computer Science 2021-04-02 Iretiayo Akinola , Jacob Varley , Dmitry Kalashnikov

The growing demand for Embodied AI and VR applications has highlighted the need for synthesizing high-quality 3D indoor scenes from sparse inputs. However, existing approaches struggle to infer massive amounts of missing geometry in large…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Dehui Wang , Congsheng Xu , Rong Wei , Yue Shi , Shoufa Chen , Dingxiang Luo , Tianshuo Yang , Xiaokang Yang , Wei Sui , Yusen Qin , Rui Tang , Yao Mu

Creating realistic virtual assets is a time-consuming process: it usually involves an artist designing the object, then spending a lot of effort on tweaking its appearance. Intricate details and certain effects, such as subsurface…

Computer Vision and Pattern Recognition · Computer Science 2022-12-13 Aljaž Božič , Denis Gladkov , Luke Doukakis , Christoph Lassner

Recent advancements in multi-view 3D reconstruction and novel-view synthesis, particularly through Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS), have greatly enhanced the fidelity and efficiency of 3D content creation.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Jun Zhou , Dinghao Li , Nannan Li , Mingjie Wang

We explain theoretically how to reconstruct the 3D scene from successive frames in order to see the video in 3D. To do this, features, associated to moving rigid objects in 3D, are extracted in frames and matched. The vanishing point…

Computer Vision and Pattern Recognition · Computer Science 2020-07-30 Slimane Larabi
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