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Semantic scene completion is the task of jointly estimating 3D geometry and semantics of objects and surfaces within a given extent. This is a particularly challenging task on real-world data that is sparse and occluded. We propose a scene…

Computer Vision and Pattern Recognition · Computer Science 2021-04-14 Christoph B. Rist , David Emmerichs , Markus Enzweiler , Dariu M. Gavrila

3D-shape reconstruction in extreme environments, such as low illumination or scattering condition, has been an open problem and intensively researched. Active stereo is one of potential solution for such environments for its robustness and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Kazuto Ichimaru , Takaki Ikeda , Diego Thomas , Takafumi Iwaguchi , Hiroshi Kawasaki

Ghost imaging (GI) is an imaging technique that uses the second-order correlation between two light beams to obtain the image of an object. However, standard GI is affected by optical background noise, which reduces its practical use. We…

Image and Video Processing · Electrical Eng. & Systems 2020-01-13 Zhe Yang , Wei-Xing Zhang , Ma-Chi Zhang , Dong Ruan , Jun-Lin Li

We present LiDAR-GS, a Gaussian Splatting (GS) method for real-time, high-fidelity re-simulation of LiDAR scans in public urban road scenes. Recent GS methods proposed for cameras have achieved significant advancements in real-time…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Qifeng Chen , Sheng Yang , Sicong Du , Tao Tang , Rengan Xie , Peng Chen , Yuchi Huo

Most existing super-resolution methods and datasets have been developed to improve the image quality in well-lighted conditions. However, these methods do not work well in real-world low-light conditions as the images captured in such…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Yang Liu , Yaofang Liu , Jinshan Pan , Yuxiang Hui , Fan Jia , Raymond H. Chan , Tieyong Zeng

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

Reasoning the 3D structure of a non-rigid dynamic scene from a single moving camera is an under-constrained problem. Inspired by the remarkable progress of neural radiance fields (NeRFs) in photo-realistic novel view synthesis of static…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Sameera Ramasinghe , Violetta Shevchenko , Gil Avraham , Anton Van Den Hengel

Neural Radiance Fields achieve high-fidelity scene representation but suffer from costly training and rendering, while 3D Gaussian splatting offers real-time performance with strong empirical results. Recently, solutions that harness the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Grzegorz Wilczyński , Mikołaj Zieliński , Krzysztof Byrski , Joanna Waczyńska , Dominik Belter , Przemysław Spurek

Particle-based representations of radiance fields such as 3D Gaussian Splatting have found great success for reconstructing and re-rendering of complex scenes. Most existing methods render particles via rasterization, projecting them to…

Achieving robust and precise pose estimation in dynamic scenes is a significant research challenge in Visual Simultaneous Localization and Mapping (SLAM). Recent advancements integrating Gaussian Splatting into SLAM systems have proven…

Robotics · Computer Science 2024-11-14 Yueming Xu , Haochen Jiang , Zhongyang Xiao , Jianfeng Feng , Li Zhang

We propose a real-time method to estimate spatiallyvarying indoor lighting from a single RGB image. Given an image and a 2D location in that image, our CNN estimates a 5th order spherical harmonic representation of the lighting at the given…

Computer Vision and Pattern Recognition · Computer Science 2019-06-11 Mathieu Garon , Kalyan Sunkavalli , Sunil Hadap , Nathan Carr , Jean-François Lalonde

The foreground segmentation algorithms suffer performance degradation in the presence of various challenges such as dynamic backgrounds, and various illumination conditions. To handle these challenges, we present a foreground segmentation…

Computer Vision and Pattern Recognition · Computer Science 2019-10-10 Maryam Sultana , Soon Ki Jung

We present a computational imaging technique for imaging thin films at grazing-incidence (GI) angles by incorporating structured illumination into existing GI X-ray scattering setups. This method involves scanning a micro-coded aperture…

Modern cameras' performance in low-light conditions remains suboptimal due to fundamental limitations in photon shot noise and sensor read noise. Generative image restoration methods have shown promising results compared to traditional…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Xijun Wang , Prateek Chennuri , Dilshan Godaliyadda , Yu Yuan , Bole Ma , Xingguang Zhang , Hamid R. Sheikh , Stanley Chan

Unwanted camera occlusions, such as debris, dust, rain-drops, and snow, can severely degrade the performance of computer-vision systems. Dynamic occlusions are particularly challenging because of the continuously changing pattern. Existing…

Computer Vision and Pattern Recognition · Computer Science 2023-08-02 Rong Zou , Manasi Muglikar , Nico Messikommer , Davide Scaramuzza

We present a fully interpretable and flexible statistical method for background subtraction in roadside LiDAR data, aimed at enhancing infrastructure-based perception in automated driving. Our approach introduces both a Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-02-18 Aitor Iglesias , Nerea Aranjuelo , Patricia Javierre , Ainhoa Menendez , Ignacio Arganda-Carreras , Marcos Nieto

Recent advancements in 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) have achieved impressive results in real-time 3D reconstruction and novel view synthesis. However, these methods struggle in large-scale, unconstrained…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Niluthpol Chowdhury Mithun , Tuan Pham , Qiao Wang , Ben Southall , Kshitij Minhas , Bogdan Matei , Stephan Mandt , Supun Samarasekera , Rakesh Kumar

We proposed Precomputed RadianceTransfer of GaussianSplats (PRTGS), a real-time high-quality relighting method for Gaussian splats in low-frequency lighting environments that captures soft shadows and interreflections by precomputing 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 Yijia Guo , Yuanxi Bai , Liwen Hu , Ziyi Guo , Mianzhi Liu , Yu Cai , Tiejun Huang , Lei Ma

In inverse rendering, accurately modeling visibility and indirect radiance for incident light is essential for capturing secondary effects. Due to the absence of a powerful Gaussian ray tracer, previous 3DGS-based methods have either…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Chun Gu , Xiaofei Wei , Zixuan Zeng , Yuxuan Yao , Li Zhang

We present a novel framework for motion planning in dynamic environments that accounts for the predicted trajectories of moving objects in the scene. We explore the use of composite signed-distance fields in motion planning and detail how…

Robotics · Computer Science 2022-02-08 Mark Nicholas Finean , Wolfgang Merkt , Ioannis Havoutis