Keyword Analysis & Research: detic

github.com

https://github.com/facebookresearch/Detic

WEBFeatures. Detects any class given class names (using CLIP ). We train the detector on ImageNet-21K dataset with 21K classes. Cross-dataset generalization to OpenImages and Objects365 without finetuning. State-of-the-art results on Open-vocabulary LVIS and Open-vocabulary COCO. Works for DETR-style detectors. Installation.

DA: 14 PA: 77 MOZ Rank: 46

dtic.mil

https://discover.dtic.mil/

WEBDefense Technical Information Center. Search this site, DoD S&T Reports, and more.. Suspension of Publishing. DTIC will temporarily suspend publishing all new submitted content to this site until further notice.

DA: 48 PA: 37 MOZ Rank: 52

arxiv.org

https://arxiv.org/abs/2201.02605

WEBJan 7, 2022 · Our results show that Detic yields excellent detectors even for classes without box annotations. It outperforms prior work on both open-vocabulary and long-tail detection benchmarks. Detic provides a gain of 2.4 mAP for all classes and 8.3 mAP for novel classes on the open-vocabulary LVIS benchmark.

DA: 2 PA: 38 MOZ Rank: 46

roboflow.com

https://blog.roboflow.com/what-is-detic/

WEBJun 16, 2023 · Detic, introduced by Facebook Research and published in January 2022, is a segmentation model specifically designed for object detection. Detic has the ability to identify 21,000 object classes with strong accuracy, including for objects that were previously challenging to detect.

DA: 99 PA: 44 MOZ Rank: 89

github.com

https://github.com/facebookresearch/Detic/blob/main/datasets/README.md

WEBmain. README.md. Detic. / datasets. README.md. Cannot retrieve latest commit at this time. History. 207 lines (163 loc) · 6.4 KB. Prepare datasets for Detic. The basic training of our model uses LVIS (which uses COCO images) and ImageNet-21K . Some models are trained on Conceptual Caption (CC3M) .

DA: 74 PA: 75 MOZ Rank: 94

marktechpost.com

https://www.marktechpost.com/2022/01/20/researchers-at-meta-and-the-university-of-texas-at-austin-propose-detic-a-method-to-detect-twenty-thousand-classes-using-image-level-supervision/

WEBJan 20, 2022 · Detic is a straightforward technique to apply image supervision in object detection with a vast vocabulary. The large-scale pretraining of CLIP benefits Detic’s generalization capabilities, and it’s unclear whether there are …

DA: 84 PA: 18 MOZ Rank: 34

arxiv.org

https://arxiv.org/pdf/2201.02605.pdf

WEBIn this paper, we propose Detector with image classes (Detic) that uses image-level supervision in addition to detection supervision. We observe that the localization and classi cation sub-problems can be decoupled. Modern region? Work done during an internship at Meta. arXiv:2201.02605v3 [cs.CV] 29 Jul 2022

DA: 46 PA: 58 MOZ Rank: 66

medium.com

https://medium.com/axinc-ai/detic-object-detection-and-segmentation-of-21k-classes-with-high-accuracy-49cba412b7d4

WEBJun 26, 2022 · Overview. Detic (Detector with Image Classes) is a segmentation model that can identify 21K object classes developed by Facebook Research and published in January 2022. It is able to detect...

DA: 93 PA: 1 MOZ Rank: 11

springer.com

https://link.springer.com/chapter/10.1007/978-3-031-20077-9_21

WEBNov 6, 2022 · We propose Detic, which simply trains the classifiers of a detector on image classification data and thus expands the vocabulary of detectors to tens of thousands of concepts. Unlike prior work, Detic does not need complex assignment schemes to assign image labels to boxes based on model predictions, making it much easier to implement …

DA: 36 PA: 77 MOZ Rank: 41

roboflow.com

https://roboflow.com/model/detic

WEBJan 7, 2022 · Detic, introduced by Facebook Research and published in January 2022, is a segmentation model specifically designed for object detection. Detic has the ability to identify 21,000 object classes with strong accuracy, including for objects that were previously challenging to detect. Reviews: 1

Reviews: 1

DA: 40 PA: 52 MOZ Rank: 29