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Occupancy prediction aims to estimate the 3D spatial distribution of occupied regions along with their corresponding semantic labels. Existing vision-based methods perform well on daytime benchmarks but struggle in nighttime scenarios due…

Computer Vision and Pattern Recognition · Computer Science 2025-10-23 Yuan Wu , Zhiqiang Yan , Yigong Zhang , Xiang Li , Jian Yang

Recently, the 3D Gaussian Splatting (3D-GS) method has achieved great success in novel view synthesis, providing real-time rendering while ensuring high-quality rendering results. However, this method faces challenges in modeling specular…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Zhiru Wang , Shiyun Xie , Chengwei Pan , Guoping Wang

With the introduction of consumer light field cameras, light field imaging has recently become widespread. However, there is an inherent trade-off between the angular and spatial resolution, and thus, these cameras often sparsely sample in…

Computer Vision and Pattern Recognition · Computer Science 2016-09-13 Nima Khademi Kalantari , Ting-Chun Wang , Ravi Ramamoorthi

We present a simple yet powerful neural network that implicitly represents and renders 3D objects and scenes only from 2D observations. The network models 3D geometries as a general radiance field, which takes a set of 2D images with camera…

Computer Vision and Pattern Recognition · Computer Science 2021-08-12 Alex Trevithick , Bo Yang

Fringe projection profilometry-based 3-D reconstruction of objects with high reflectivity and low surface roughness remains a significant challenge. When measuring such glossy surfaces, specular reflection and indirect illumination often…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Sanghoon Jeon , Gihyun Jung , Suhyeon Ka , Jae-Sang Hyun

We present a method that tackles the challenge of predicting color and depth behind the visible content of an image. Our approach aims at building up a Layered Depth Image (LDI) from a single RGB input, which is an efficient representation…

Computer Vision and Pattern Recognition · Computer Science 2019-08-27 Helisa Dhamo , Nassir Navab , Federico Tombari

A surface light field represents the radiance of rays originating from any points on the surface in any directions. Traditional approaches require ultra-dense sampling to ensure the rendering quality. In this paper, we present a novel…

Computational Geometry · Computer Science 2018-10-16 Anpei Chen , Minye Wu , Yingliang Zhang , Nianyi Li , Jie Lu , Shenghua Gao , Jingyi Yu

We introduce a framework for learning latent representations of 4D objects which are descriptive, faithfully capturing object geometry and appearance; compressive, aiding in downstream efficiency; and accessible, requiring minimal input,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Anagh Malik , Dorian Chan , Xiaoming Zhao , David B. Lindell , Oncel Tuzel , Jen-Hao Rick Chang

Visual perception is a challenging problem in part due to illumination variations. A possible solution is to first estimate an illumination invariant representation before using it for recognition. The object albedo and surface normals are…

Computer Vision and Pattern Recognition · Computer Science 2012-07-03 Yichuan Tang , Ruslan Salakhutdinov , Geoffrey Hinton

Recently, several approaches have emerged for generating neural representations with multiple levels of detail (LODs). LODs can improve the rendering by using lower resolutions and smaller model sizes when appropriate. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2023-09-22 David Li , Brandon Y. Feng , Amitabh Varshney

Recent works on implicit neural representations have shown promising results for multi-view surface reconstruction. However, most approaches are limited to relatively simple geometries and usually require clean object masks for…

Computer Vision and Pattern Recognition · Computer Science 2021-08-24 Jingyang Zhang , Yao Yao , Long Quan

We introduce latent intuitive physics, a transfer learning framework for physics simulation that can infer hidden properties of fluids from a single 3D video and simulate the observed fluid in novel scenes. Our key insight is to use latent…

Artificial Intelligence · Computer Science 2024-08-06 Xiangming Zhu , Huayu Deng , Haochen Yuan , Yunbo Wang , Xiaokang Yang

Learning-based 3D reconstruction methods have shown impressive results. However, most methods require 3D supervision which is often hard to obtain for real-world datasets. Recently, several works have proposed differentiable rendering…

Computer Vision and Pattern Recognition · Computer Science 2020-03-24 Michael Niemeyer , Lars Mescheder , Michael Oechsle , Andreas Geiger

In this paper, we present a new Light Field representation for efficient Light Field processing and rendering called Fourier Disparity Layers (FDL). The proposed FDL representation samples the Light Field in the depth (or equivalently the…

Computer Vision and Pattern Recognition · Computer Science 2019-10-02 Mikael Le Pendu , Christine Guillemot , Aljosa Smolic

The advancement of generative radiance fields has pushed the boundary of 3D-aware image synthesis. Motivated by the observation that a 3D object should look realistic from multiple viewpoints, these methods introduce a multi-view constraint…

Computer Vision and Pattern Recognition · Computer Science 2021-12-10 Xingang Pan , Xudong Xu , Chen Change Loy , Christian Theobalt , Bo Dai

We propose a novel framework to automatically learn to aggregate and transform photometric measurements from multiple unstructured views into spatially distinctive and view-invariant low-level features, which are subsequently fed to a…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Xiang Feng , Kaizhang Kang , Fan Pei , Huakeng Ding , Jinjiang You , Ping Tan , Kun Zhou , Hongzhi Wu

Visual localization techniques rely upon some underlying scene representation to localize against. These representations can be explicit such as 3D SFM map or implicit, such as a neural network that learns to encode the scene. The former…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Maxime Pietrantoni , Gabriela Csurka , Martin Humenberger , Torsten Sattler

In this article we develop an image based rendering technique based on light field reconstruction from a limited set of perspective views acquired by cameras. Our approach utilizes sparse representation of epipolar-plane images in a…

Computer Vision and Pattern Recognition · Computer Science 2015-10-01 Suren Vagharshakyan , Robert Bregovic , Atanas Gotchev

3D reconstruction and relighting of objects made from scattering materials present a significant challenge due to the complex light transport beneath the surface. 3D Gaussian Splatting introduced high-quality novel view synthesis at…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Jan-Niklas Dihlmann , Arjun Majumdar , Andreas Engelhardt , Raphael Braun , Hendrik P. A. Lensch

Reconstructing the geometry and appearance of objects from photographs taken in different environments is difficult as the illumination and therefore the object appearance vary across captured images. This is particularly challenging for…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Hadi Alzayer , Philipp Henzler , Jonathan T. Barron , Jia-Bin Huang , Pratul P. Srinivasan , Dor Verbin