Research map / 3D vision / Depth and stereo
A Perceptual Measure for Deep Single Image Camera Calibration
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the proposed calibration network rather than the two compared methods | Virtual object insertion · User study, 69 images | share of votes: 46% vs 31% and 23% | Helped |
| Estimate camera parameters with the proposed network | SUN360 test set · SUN360 test set | third-quartile human sensitivity: under 20% | Helped |
| Underestimate field of view, by up to the reported tolerated range | Virtual object insertion · Human perception study | human detection of calibration error: 15° over and up to 50° under | No clear effect |
| Introduce roll error of 12° or more | Virtual object insertion · Human perception study | human detection of calibration error: 12° and more | Hurt |
| Keep roll error within approximately ±2.5° | Virtual object insertion · Human perception study | human detection of calibration error: ±2.5° | No clear effect |
Closest papers by meaning
- CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View Depth (CVPR 2019 · similarity 0.88)
- Perspective Fields for Single Image Camera Calibration (CVPR 2023 · similarity 0.86)
- On the Calibration of Human Pose Estimation (ICML 2024 · similarity 0.84)
- Zero-Shot Scene Reconstruction from Single Images with Deep Prior Assembly (NeurIPS 2024 · similarity 0.84)
- LEAP: Liberate Sparse-View 3D Modeling from Camera Poses (ICLR 2024 · similarity 0.84)
- The 3D-PC: a benchmark for visual perspective taking in humans and machines (ICLR 2025 · similarity 0.83)
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