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Related papers: Seeing the World through Your Eyes

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Creating high-quality and realistic images is now possible thanks to the impressive advancements in image generation. A description in natural language of your desired output is all you need to obtain breathtaking results. However, as the…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Giuseppe Cartella , Vittorio Cuculo , Marcella Cornia , Rita Cucchiara

This paper introduces single-image geometric and appearance reconstruction from water reflection photography, i.e., images capturing direct and water-reflected real-world scenes. Water reflection offers an additional viewpoint to the direct…

Computer Vision and Pattern Recognition · Computer Science 2020-01-08 Ryo Kawahara , Meng-Yu Jennifer Kuo , Shohei Nobuhara , Ko Nishino

Refractive Index Tomography is the inverse problem of reconstructing the continuously-varying 3D refractive index in a scene using 2D projected image measurements. Although a purely refractive field is not directly visible, it bends light…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Brandon Zhao , Aviad Levis , Liam Connor , Pratul P. Srinivasan , Katherine L. Bouman

The idea of 3D reconstruction as scene understanding is foundational in computer vision. Reconstructing 3D scenes from 2D visual observations requires strong priors to disambiguate structure. Much work has been focused on the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Peter Kulits , Michael J. Black , Silvia Zuffi

We address the dual problems of novel view synthesis and environment reconstruction from hand-held RGBD sensors. Our contributions include 1) modeling highly specular objects, 2) modeling inter-reflections and Fresnel effects, and 3)…

Computer Vision and Pattern Recognition · Computer Science 2020-06-16 Jeong Joon Park , Aleksander Holynski , Steve Seitz

Computational ghost imaging retrieves the spatial information of a scene using a single pixel detector. By projecting a series of known random patterns and measuring the back reflected intensity for each one, it is possible to reconstruct a…

Existing methods for reconstructing objects and humans from a monocular image suffer from severe mesh collisions and performance limitations for interacting occluding objects. This paper introduces a method to obtain a globally consistent…

Computer Vision and Pattern Recognition · Computer Science 2024-08-16 Sarthak Batra , Partha P. Chakrabarti , Simon Hadfield , Armin Mustafa

We present a learning-based approach for removing unwanted obstructions, such as window reflections, fence occlusions or raindrops, from a short sequence of images captured by a moving camera. Our method leverages the motion differences…

Computer Vision and Pattern Recognition · Computer Science 2020-04-03 Yu-Lun Liu , Wei-Sheng Lai , Ming-Hsuan Yang , Yung-Yu Chuang , Jia-Bin Huang

We propose a method for in-hand 3D scanning of an unknown object with a monocular camera. Our method relies on a neural implicit surface representation that captures both the geometry and the appearance of the object, however, by contrast…

Computer Vision and Pattern Recognition · Computer Science 2023-06-23 Shreyas Hampali , Tomas Hodan , Luan Tran , Lingni Ma , Cem Keskin , Vincent Lepetit

We present a method that takes as input a set of images of a scene illuminated by unconstrained known lighting, and produces as output a 3D representation that can be rendered from novel viewpoints under arbitrary lighting conditions. Our…

Computer Vision and Pattern Recognition · Computer Science 2020-12-08 Pratul P. Srinivasan , Boyang Deng , Xiuming Zhang , Matthew Tancik , Ben Mildenhall , Jonathan T. Barron

Learning neural radiance fields of a scene has recently allowed realistic novel view synthesis of the scene, but they are limited to synthesize images under the original fixed lighting condition. Therefore, they are not flexible for the…

Computer Vision and Pattern Recognition · Computer Science 2021-10-26 Quan Zheng , Gurprit Singh , Hans-Peter Seidel

Synthesizing novel views for urban environments is crucial for tasks like autonomous driving and virtual tours. Compared to object-level or indoor situations, outdoor settings present unique challenges, such as inconsistency across frames…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Mreenav Shyam Deka , Lu Sang , Daniel Cremers

We propose a method to estimate 3D human poses from substantially blurred images. The key idea is to tackle the inverse problem of image deblurring by modeling the forward problem with a 3D human model, a texture map, and a sequence of…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Yiming Zhao , Denys Rozumnyi , Jie Song , Otmar Hilliges , Marc Pollefeys , Martin R. Oswald

The goal of this work is to perform 3D reconstruction and novel view synthesis from data captured by scanning platforms commonly deployed for world mapping in urban outdoor environments (e.g., Street View). Given a sequence of posed RGB…

Computer Vision and Pattern Recognition · Computer Science 2021-11-30 Konstantinos Rematas , Andrew Liu , Pratul P. Srinivasan , Jonathan T. Barron , Andrea Tagliasacchi , Thomas Funkhouser , Vittorio Ferrari

This paper introduces a novel pipeline to reconstruct the geometry of interacting multi-person in clothing on a globally coherent scene space from a single image. The main challenge arises from the occlusion: a part of a human body is not…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Junuk Cha , Hansol Lee , Jaewon Kim , Nhat Nguyen Bao Truong , Jae Shin Yoon , Seungryul Baek

Humans are in constant contact with the world as they move through it and interact with it. This contact is a vital source of information for understanding 3D humans, 3D scenes, and the interactions between them. In fact, we demonstrate…

Computer Vision and Pattern Recognition · Computer Science 2022-03-30 Hongwei Yi , Chun-Hao P. Huang , Dimitrios Tzionas , Muhammed Kocabas , Mohamed Hassan , Siyu Tang , Justus Thies , Michael J. Black

3D reconstruction methods such as Neural Radiance Fields (NeRFs) excel at rendering photorealistic novel views of complex scenes. However, recovering a high-quality NeRF typically requires tens to hundreds of input images, resulting in a…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Rundi Wu , Ben Mildenhall , Philipp Henzler , Keunhong Park , Ruiqi Gao , Daniel Watson , Pratul P. Srinivasan , Dor Verbin , Jonathan T. Barron , Ben Poole , Aleksander Holynski

In this paper, we present a method to reconstruct the world and multiple dynamic humans in 3D from a monocular video input. As a key idea, we represent both the world and multiple humans via the recently emerging 3D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Inhee Lee , Byungjun Kim , Hanbyul Joo

Gaze correction aims to redirect the person's gaze into the camera by manipulating the eye region, and it can be considered as a specific image resynthesis problem. Gaze correction has a wide range of applications in real life, such as…

Computer Vision and Pattern Recognition · Computer Science 2019-06-04 Jichao Zhang , Meng Sun , Jingjing Chen , Hao Tang , Yan Yan , Xueying Qin , Nicu Sebe

Radiance fields have emerged as powerful tools for 3D scene reconstruction. However, casual capture remains challenging due to the narrow field of view of perspective cameras, which limits viewpoint coverage and feature correspondences…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Yalda Foroutan , Ipek Oztas , Daniel Rebain , Aysegul Dundar , Kwang Moo Yi , Lily Goli , Andrea Tagliasacchi
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