Research map / Detection and segmentation / CNN features
BRISKS: Binary Features for Spherical Images on a Geodesic Grid
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use BRISKS instead of SSIFT | Spherical-image feature detection · Synthetic images, rotation and translation | repeatability: 0.65 -> 0.93 | Helped |
| Use BRISKS instead of SIFT on equirectangular images | Spherical-image feature detection · Synthetic images, rotation and translation | repeatability: 0.57 -> 0.93 | Helped |
| Use BRISKS instead of SSIFT | Spherical-image feature detection · Synthetic images, illumination change | repeatability: 0.49 -> 0.64 | Helped |
| Use BRISKS instead of SIFT on equirectangular images | Spherical-image feature detection · Synthetic images, illumination change | repeatability: 0.41 -> 0.64 | Helped |
| Use BRISKS instead of SSIFT | Spherical-image feature detection · SUN360, rotation | repeatability: 0.86 -> 0.94 | Helped |
| Use BRISKS instead of SIFT on equirectangular images | Spherical-image feature detection · SUN360, rotation | repeatability: 0.70 -> 0.94 | Helped |
| Use BRISKS instead of SSIFT | Spherical-image feature detection · SUN360, noise 10dB | repeatability: 0.76 -> 0.90 | Helped |
| Use BRISKS instead of SIFT on equirectangular images | Spherical-image feature detection · SUN360, noise 10dB | repeatability: 0.65 -> 0.90 | Helped |
| Use BRISKS instead of SSIFT | Spherical-image feature detection · SUN360, noise 15dB | repeatability: 0.79 -> 0.93 | Helped |
| Use BRISKS instead of SIFT on equirectangular images | Spherical-image feature detection · SUN360, noise 15dB | repeatability: 0.67 -> 0.93 | Helped |
| Use BRISKS instead of SSIFT | Spherical-image feature detection · SUN360, noise 20dB | repeatability: 0.83 -> 0.93 | Helped |
| Use BRISKS instead of SIFT on equirectangular images | Spherical-image feature detection · SUN360, noise 20dB | repeatability: 0.66 -> 0.93 | Helped |
Closest papers by meaning
- Tangent Images for Mitigating Spherical Distortion (CVPR 2020 · similarity 0.87)
- Spherical Criteria for Fast and Accurate 360° Object Detection (AAAI 2020 · similarity 0.85)
- Unified Spherical Frontend: Learning Rotation-Equivariant Representations of Spherical Images from Any Camera (CVPR 2026 · similarity 0.85)
- Attention on the Sphere (NeurIPS 2025 · similarity 0.85)
- Spherical Mask: Coarse-to-Fine 3D Point Cloud Instance Segmentation with Spherical Representation (CVPR 2024 · similarity 0.84)
- Stereographic Spherical Sliced Wasserstein Distances (ICML 2024 · similarity 0.82)
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