Unsupervised Learning for Structure from Motion
Perception of depth, ego-motion and robust keypoints is critical for SLAM andstructure from motion applications. Neural networks have achieved great perfor-mance in perception tasks in recent years. But collecting labeled data for super-vised training is labor intensive and costly. This thesis explo...
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| Format: | Others |
| Language: | English |
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Linköpings universitet, Datorseende
2021
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-173731 |