Auto-Rectify Network for Unsupervised Indoor Depth Estimation
Single-View depth estimation using the CNNs trained from unlabelled videos has shown significant promise. However, excellent results have mostly been obtained in street-scene driving scenarios, and such methods often fail in other settings, particularly indoor videos taken by handheld devices. In th...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 44(2022), 12 vom: 02. Dez., Seite 9802-9813
|
|---|
| 1. Verfasser: |
Bian, Jia-Wang
(VerfasserIn) |
|---|
| Weitere Verfasser: |
Zhan, Huangying,
Wang, Naiyan,
Chin, Tat-Jun,
Shen, Chunhua,
Reid, Ian |
|---|
| Format: | Online-Aufsatz
|
|---|
| Sprache: | English |
|---|
| Veröffentlicht: |
2022
|
|---|
| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
|
|---|
| Schlagworte: | Journal Article
Research Support, Non-U.S. Gov't |
|---|