![R]Group-Free 3D Object Detector: New SOTA on ScanNet V2(69.1 mAP@0.25, 52.8@mAP@0.5) and SUN RGB-D(62.8 mAP@0.25 and 42.3 mAP@0.5)🔥 : r/MachineLearning R]Group-Free 3D Object Detector: New SOTA on ScanNet V2(69.1 mAP@0.25, 52.8@mAP@0.5) and SUN RGB-D(62.8 mAP@0.25 and 42.3 mAP@0.5)🔥 : r/MachineLearning](https://preview.redd.it/m6rbt1f6l2s61.png?width=524&format=png&auto=webp&s=37c77b021b7a7f14d44c52210ad4e2fc3607a7b1)
R]Group-Free 3D Object Detector: New SOTA on ScanNet V2(69.1 mAP@0.25, 52.8@mAP@0.5) and SUN RGB-D(62.8 mAP@0.25 and 42.3 mAP@0.5)🔥 : r/MachineLearning
Overlap - Her er resultatet af Johannes og mit arbejde i sidste uge... Den færdige tegning fylder knap 3 meter i længden, 1 meter i højden. Nu er den scannet, og min
![PDF] Fast ScanNet: Fast and Dense Analysis of Multi-Gigapixel Whole-Slide Images for Cancer Metastasis Detection | Semantic Scholar PDF] Fast ScanNet: Fast and Dense Analysis of Multi-Gigapixel Whole-Slide Images for Cancer Metastasis Detection | Semantic Scholar](https://d3i71xaburhd42.cloudfront.net/e0a711d111eb0373a06d46bbe26b710f7c924ccb/8-TableIII-1.png)
PDF] Fast ScanNet: Fast and Dense Analysis of Multi-Gigapixel Whole-Slide Images for Cancer Metastasis Detection | Semantic Scholar
![PDF] Fast ScanNet: Fast and Dense Analysis of Multi-Gigapixel Whole-Slide Images for Cancer Metastasis Detection | Semantic Scholar PDF] Fast ScanNet: Fast and Dense Analysis of Multi-Gigapixel Whole-Slide Images for Cancer Metastasis Detection | Semantic Scholar](https://d3i71xaburhd42.cloudfront.net/e0a711d111eb0373a06d46bbe26b710f7c924ccb/9-Figure11-1.png)