Media Summary: CVPR 2021 presentation. Publication: MonoRec: Hyeonjoong Jang, Dongyoung Choi, Donggun Kim, Woohyun Kang, Min H. Kim (2025) “Splat-based Authors: Johanna Wald, Helisa Dhamo, Nassir Navab, Federico Tombari Description:

Semi Supervised 3d Scene Reconstruction - Detailed Analysis & Overview

CVPR 2021 presentation. Publication: MonoRec: Hyeonjoong Jang, Dongyoung Choi, Donggun Kim, Woohyun Kang, Min H. Kim (2025) “Splat-based Authors: Johanna Wald, Helisa Dhamo, Nassir Navab, Federico Tombari Description:

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Semi-Supervised 3D-Scene Reconstruction in Dynamic Environments from Single Camera
SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields
SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields
RetrievalFuse: Neural 3D Scene Reconstruction with a Database (ICCV'2021)
Semantic Implicit Neural Scene Representations with Semi-supervised Training | 3DV 2020
[CVPR 2021] MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from One Camera
Learning 3D Scene Priors with 2D Supervision (CVPR'2023)
CVPR 2023 Paper: VisFusion - Visibility-aware Online 3D Scene Reconstruction from Videos (Gao et al)
NimbusGS: Unified 3D Scene Reconstruction under Hybrid Weather
[ICCV2025 Supplemental Video] Splat-based 3D Scene Reconstruction with Extreme Motion-blur
Learning 3D Semantic Scene Graphs From 3D Indoor Reconstructions
3D scene reconstruction with Stereo vision and Open3D reconstruction system on Jetson Nano.
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Semi-Supervised 3D-Scene Reconstruction in Dynamic Environments from Single Camera

Semi-Supervised 3D-Scene Reconstruction in Dynamic Environments from Single Camera

Semi

SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields

SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields

3D reconstruction

SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields

SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields

SceneRF: Self-

RetrievalFuse: Neural 3D Scene Reconstruction with a Database (ICCV'2021)

RetrievalFuse: Neural 3D Scene Reconstruction with a Database (ICCV'2021)

Project: https://nihalsid.github.io/retrieval-fuse/ Paper: http://arxiv.org/pdf/2104.00024

Semantic Implicit Neural Scene Representations with Semi-supervised Training | 3DV 2020

Semantic Implicit Neural Scene Representations with Semi-supervised Training | 3DV 2020

Biological vision infers multi-modal

[CVPR 2021] MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from One Camera

[CVPR 2021] MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from One Camera

CVPR 2021 presentation. Publication: MonoRec:

Learning 3D Scene Priors with 2D Supervision (CVPR'2023)

Learning 3D Scene Priors with 2D Supervision (CVPR'2023)

Project: https://yinyunie.github.io/sceneprior-page/ Holistic

CVPR 2023 Paper: VisFusion - Visibility-aware Online 3D Scene Reconstruction from Videos (Gao et al)

CVPR 2023 Paper: VisFusion - Visibility-aware Online 3D Scene Reconstruction from Videos (Gao et al)

VisFusion: Visibility-aware Online

NimbusGS: Unified 3D Scene Reconstruction under Hybrid Weather

NimbusGS: Unified 3D Scene Reconstruction under Hybrid Weather

CVPR 2026.

[ICCV2025 Supplemental Video] Splat-based 3D Scene Reconstruction with Extreme Motion-blur

[ICCV2025 Supplemental Video] Splat-based 3D Scene Reconstruction with Extreme Motion-blur

Hyeonjoong Jang, Dongyoung Choi, Donggun Kim, Woohyun Kang, Min H. Kim (2025) “Splat-based

Learning 3D Semantic Scene Graphs From 3D Indoor Reconstructions

Learning 3D Semantic Scene Graphs From 3D Indoor Reconstructions

Authors: Johanna Wald, Helisa Dhamo, Nassir Navab, Federico Tombari Description:

3D scene reconstruction with Stereo vision and Open3D reconstruction system on Jetson Nano.

3D scene reconstruction with Stereo vision and Open3D reconstruction system on Jetson Nano.

A demo of

Self-supervised Single-view 3D Reconstruction via Semantic Consistency

Self-supervised Single-view 3D Reconstruction via Semantic Consistency

Introducing "Self-