1. Home | Free Poker Network(FPN)
Players · FPN Leagues · Join/Login · Venues
Official website of the Free Poker Network featuring poker tournament coverage of events, schedules and news
2. Leaderboard | MaCVi
Panoptic FPN (RN-50), 21.7, V100, 40.1, 21.7, 89.3, 46.9, 73.5, 58.9. 5, University of Ljubljana, Panoptic FPN (RN-101), 16.7, V100, 38.7, 19.7, 89.4, 45.0 ...
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3. Board of Examiners | AskPsy.nl
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Rules & Regulations » Board of Examiners
4. COCO test-dev Benchmark (Object Detection) - Papers With Code
Object Detection on COCO test-dev. Leaderboard; Dataset. View. box mAP, AP50 ... FPN) Mask R-CNN (ResNeXt-101-FPN) RetinaNet (ResNeXt-101-FPN) RetinaNet ...
The current state-of-the-art on COCO test-dev is Co-DETR. See a full comparison of 261 papers with code.
5. Leaderboard - MaCVi
Panoptic FPN (RN-101), 16.7, V100, 38.7, 19.7, 89.4, 45.0, 73.6, 58.1. 3, University of Ljubljana, Panoptic FPN (RN-50), 21.7, V100, 40.1, 21.7, 89.3, 46.9 ...
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6. Free Poker Network - Facebook
FPN's Tag Team Championship features FPN League players from around the country for the final qualifier of FPN's Step In The Ring promotion. Players can win ...
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7. COCO test-dev Benchmark (Panoptic Segmentation) - Papers With Code
Panoptic Segmentation on COCO test-dev. Leaderboard; Dataset. View. PQ, PQst ... FPN) AUNet (ResNext-152-FPN) UPSNet (ResNet-101-FPN) UPSNet (ResNet-101 ...
The current state-of-the-art on COCO test-dev is Mask DINO (single scale). See a full comparison of 38 papers with code.
8. FPN-Illinois poker forum | Facebook
This is a place where we can share information, or suggestions. Post if you find deals on airfare, hotels, or recent wins at nightly establishments....
See posts, photos and more on Facebook.
9. Leaderboard of incremental learning — Ianvs v0.1 documentation
12 jul 2022 · Single Task Learning: FPN · Incremental Learning: BasicIL-FPN. ROADMAP. Roadmap · Ianvs. » Leaderboard of incremental learning; Edit on GitHub.
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10. Multi-Scale PointPillars 3D Object Detection Network - Semantic Scholar
... leaderboard. Point cloud object detection is a key step in many 3D ... (FPN) and deformable convolution, our region proposal network achieves high ...
Inspired by feature pyramid networks (FPN) and deformable convolution, the proposed MPNet achieves high accuracy while keeps high speed, and is the most efficient model compared within the top 10 models in the Bird's Eye View leaderboard. Point cloud object detection is a key step in many 3D applications, such as autonomous driving and housekeeping robots. In this paper, we present MPNet, a Multi-Scale PointPillars Network for 3D object detection using point clouds. This paper aims at high accuracy and efficient speed. The proposed neural network is mainly composed of three part, a feature extracting part, a region proposal network, and finally a detection head. We use multi-scale encoders to concurrently extract features by PointNet, and then treat the 3D feature map as a pseudo image with many channels. Inspired by feature pyramid networks (FPN) and deformable convolution, our region proposal network achieves high accuracy while keeps high speed. MPNet combines features with different receptive field, and accelerates model by using 2D convolution, balancing the accuracy and speed well. Experiments on KITTI car detection benchmark show that our MPNet captures better location information on the bird's eye view. It ranks the third place in the Bird's Eye View Leaderboard. Meanwhile, it is the most efficient model compared within the top 10 models in the Bird's Eye View leaderboard.
11. Organisational structure - About UM - Maastricht University
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The Faculty of Psychology and Neuroscience (FPN) has two main tasks: to organise and carry out education and research. Ultimate responsibility rests with the Dean, who sits on the Faculty Board together with the three members for research and valorisation, education, and innovation and internationalisation. The board is advised by a democratically elected representation body, the Faculty Council.
12. ViTDet - Hugging Face
Surprisingly, we observe: (i) it is sufficient to build a simple feature pyramid from a single-scale feature map (without the common FPN design) and (ii) it ...
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