Research map / Detection and segmentation / CNN features
Predicting Ground-Level Scene Layout From Aerial Imagery
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Initialize VGG16 with cross-view pre-training rather than random weights | ISPRS aerial-image segmentation · ISPRS segmentation, 82 training samples, Building | average precision: 0.71 -> 0.78 | Helped |
| Initialize VGG16 with cross-view pre-training rather than random weights | ISPRS aerial-image segmentation · ISPRS segmentation, 82 training samples, Low vegetation | average precision: 0.64 -> 0.67 | Helped |
| Initialize VGG16 with cross-view pre-training rather than random weights | ISPRS aerial-image segmentation · ISPRS segmentation, 82 training samples, Impervious surfaces | average precision: 0.73 -> 0.64 | Hurt |
| Initialize VGG16 with cross-view pre-training rather than random weights | ISPRS aerial-image segmentation · ISPRS segmentation, 82 training samples, Car | average precision: 0.57 -> 0.49 | Hurt |
| Initialize VGG16 with cross-view pre-training rather than random weights | ISPRS aerial-image segmentation · ISPRS segmentation, 82 training samples, Tree | average precision: 0.74 -> 0.74 | No clear effect |
Closest papers by meaning
- PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation (CVPR 2021 · similarity 0.88)
- Aerial Lifting: Neural Urban Semantic and Building Instance Lifting from Aerial Imagery (CVPR 2024 · similarity 0.88)
- SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation (CVPR 2024 · similarity 0.87)
- Learnable Earth Parser: Discovering 3D Prototypes in Aerial Scans (CVPR 2024 · similarity 0.85)
- Unsupervised Semantic Segmentation Through Depth-Guided Feature Correlation and Sampling (CVPR 2024 · similarity 0.85)
- SemStereo: Semantic-Constrained Stereo Matching Network for Remote Sensing (AAAI 2025 · similarity 0.84)
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