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Richard Szeliski

7 accepted papers

2026

ORBIT: Benchmarking SfM in the Wild with 360deg Video

CVPR 2026

Structure-from-Motion (SfM) is a cornerstone of 3D perception, yet current methods often fail when applied to complex videos involving challenging camera motions or dynamic scenes.Compounding the problem, the field lacks reliable ground-truth benchmarks for such difficult scenarios, making it hard t

Cited by 0SourceScholar
2024

UniSDF: Unifying Neural Representations for High-Fidelity 3D Reconstruction of Complex Scenes with Reflections

NeurIPS 2024poster

Neural 3D scene representations have shown great potential for 3D reconstruction from 2D images. However, reconstructing real-world captures of complex scenes still remains a challenge. Existing generic 3D reconstruction methods often struggle to represent fine geometric details and do not adequatel…

2023

Accidental Light Probes

CVPR 2023poster

Recovering lighting in a scene from a single image is a fundamental problem in computer vision. While a mirror ball light probe can capture omnidirectional lighting, light probes are generally unavailable in everyday images. In this work, we study recovering lighting from accidental light probes (AL…

Cited by 15SourcePDFScholar
2020

SynSin: End-to-End View Synthesis From a Single Image

CVPR 2020oral

View synthesis allows for the generation of new views of a scene given one or more images. This is challenging; it requires comprehensively understanding the 3D scene from images. As a result, current methods typically use multiple images, train on ground-truth depth, or are limited to synthetic dat…

Cited by 510PDFcodeScholar
2020

VPLNet: Deep Single View Normal Estimation With Vanishing Points and Lines

CVPR 2020poster

We present a novel single-view surface normal estimation method that combines traditional line and vanishing point analysis with a deep learning approach. Starting from a color image and a Manhattan line map, we use a deep neural network to regress on a dense normal map, and a dense Manhattan label…

Cited by 47PDFScholar
2015

Model-Based Tracking at 300Hz Using Raw Time-of-Flight Observations

ICCV 2015poster

Consumer depth cameras have dramatically improved our ability to track rigid, articulated, and deformable 3D objects in real-time. However, depth cameras have a limited temporal resolution (frame-rate) that restricts the accuracy and robustness of tracking, especially for fast or unpredictable motio…

Cited by 23PDFScholar