nianticlabs

[ICCV 2019] Monocular depth estimation from a single image

[ECCV 2022] SimpleRecon: 3D Reconstruction Without 3D Convolutions

File format for 3D Gaussian splats. About 10x smaller than the PLY equivalent with virtually no perceptible loss in visual quality. Offered as open source by Niantic Labs. More details at...

[ECCV 2024 - Oral] ACE0 is a learning-based structure-from-motion approach that estimates camera parameters of sets of images by learning a multi-view consistent, implicit scene representation.

[CVPR 2021] Self-supervised depth estimation from short sequences

[CVPR 2024 - Oral] Matching 2D Images in 3D: Metric Relative Pose from Metric Correspondences

[CVPR 2023 - Highlight] Accelerated Coordinate Encoding (ACE): Learning to Relocalize in Minutes using RGB and Poses

[ECCV 2020] Learning stereo from single images using monocular depth estimation networks

A flexible threat detection platform that simplifies rule management and deployment using K8s CronJob and Helm, but can also run standalone or with other job schedulers like Nomad.

[ECCV 2022] Map-free Visual Relocalization: Metric Pose Relative to a Single Image

[CVPR 2023] DiffusioNeRF: Regularizing Neural Radiance Fields with Denoising Diffusion Models

[CVPR 2021] Monocular depth estimation using wavelets for efficiency

[CVPR 2020] Estimation of the visible and hidden traversable space from a single color image

[CVPR 2024 Highlight] Map-Relative Pose Regression for Visual Re-Localization

[ECCV 2024] DoubleTake: Geometry Guided Depth Estimation

[ICCV 2019] Depth Hints are complementary depth suggestions which improve monocular depth estimation algorithms trained from stereo pairs

[CVPR 2023] Removing Objects From Neural Radiance Fields

[CVPR 2023] Virtual Occlusions Through Implicit Depth

[CVPR 2024] AirPlanes: Accurate Plane Estimation via 3D-Consistent Embeddings

[CVPR 2023] Two-view Geometry Scoring Without Correspondences

[ICCV 2025] PlaceIt3D: Language-Guided Object Placement in Real 3D Scenes

[ECCV 2020] Single image depth prediction allows us to rectify planar surfaces in images and extract view-invariant local features for better feature matching

[ECCV 2020] Training neural networks to predict visual overlap of images, through interpretable non-metric box embeddings

[CVPR 2021] Forecasting the panoptic segmentation of future video frames