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[paper](https://arxiv.org/abs/1311.2524) | [code](https://github.com/rbgirshick/rcnn)\n2   | Fast R-CNN    | 2015 | [paper](https://arxiv.org/abs/1504.08083) | [code](https://github.com/rbgirshick/fast-rcnn)\n3   | Faster R-CNN    | 2015 | [paper](https://arxiv.org/abs/1506.01497) | [code](https://github.com/jwyang/faster-rcnn.pytorch)\n4   | CMS-RCNN    | 2016 | [paper](https://arxiv.org/pdf/1606.05413v1.pdf) | code\n5   | Mask R-CNN   | 2017 | [paper](https://arxiv.org/abs/1703.06870#:~:text=The%20method%2C%20called%20Mask%20R,CNN%2C%20running%20at%205%20fps.) | [code1](https://github.com/matterport/Mask_RCNN) , [code2](https://github.com/multimodallearning/pytorch-mask-rcnn)\n6   |  Revisting R-CNN   | 2018 | [paper](https://www.ecva.net/papers/eccv_2018/papers_ECCV/papers/Bowen_Cheng_Revisiting_RCNN_On_ECCV_2018_paper.pdf) | [code](https://github.com/SHI-Labs/Decoupled-Classification-Refinement)\n7   | Plane R-CNN   | 2018 | [paper](https://arxiv.org/abs/1812.04072) | [code](https://github.com/NVlabs/planercnn)\n8   | PointRCNN | 2018 | [paper](https://arxiv.org/abs/1812.04244) | [code](https://github.com/sshaoshuai/PointRCNN)\n9   | 3D-RCNN | 2018 | [paper](https://openaccess.thecvf.com/content_cvpr_2018/papers/Kundu_3D-RCNN_Instance-Level_3D_CVPR_2018_paper.pdf) | code not available\n10   | SAM-RCNN  | 2018 | [paper](https://arxiv.org/abs/1808.02246v1) | Code not available\n11  | MITOS-RCNN  | 2018 | [paper](https://arxiv.org/pdf/1807.01788v1.pdf) | Code not available\n12   | Reasoning R-CNN   | 2019 | [paper](https://openaccess.thecvf.com/content_CVPR_2019/papers/Xu_Reasoning-RCNN_Unifying_Adaptive_Global_Reasoning_Into_Large-Scale_Object_Detection_CVPR_2019_paper.pdf) | [code](https://github.com/chanyn/Reasoning-RCNN)\n13   | Stereo R-CNN   | 2019 | [paper](https://arxiv.org/pdf/1902.09738v2.pdf) | [code](https://github.com/HKUST-Aerial-Robotics/Stereo-RCNN)\n14   | NOTE-RCNN | 2019 | [paper](https://arxiv.org/abs/1812.00124v1) | Code not available\n15   | PI-RCNN | 2019 | [paper](https://arxiv.org/pdf/1911.06084v3.pdf) | Code not available\n16   | PV-R-CNN   | 2020 | [paper](https://arxiv.org/abs/1912.13192) | [code](https://github.com/sshaoshuai/PV-RCNN)\n17   | Siam R-CNN   | 2020 | [paper](https://arxiv.org/abs/1911.12836) | [code](https://github.com/VisualComputingInstitute/SiamR-CNN)\n18   | Context-Aware RCNN   | 2020 | [paper](https://arxiv.org/pdf/2007.09861v1.pdf) | [code](https://github.com/MCG-NJU/CRCNN-Action)\n19   | Track-RCNN  | 2020 | [paper](https://arxiv.org/pdf/2004.07786v1.pdf) | Code not available\n20   | Universal-RCNN  | 2020 | [paper](https://arxiv.org/abs/2002.07417v1) | Code not available\n21   | PS-RCNN  | 2020 | [paper](https://arxiv.org/pdf/2003.07080v1.pdf) | Code not available\n22   | RCNN-SliceNet  | 2021 | [paper](https://openaccess.thecvf.com/content/CVPR2021W/CVMI/html/Wu_RCNN-SliceNet_A_Slice_and_Cluster_Approach_for_Nuclei_Centroid_Detection_CVPRW_2021_paper.html) | Code not available\n\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fajithvcoder%2Fawesome-rcnn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fajithvcoder%2Fawesome-rcnn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fajithvcoder%2Fawesome-rcnn/lists"}