| SLNo | Architecture_Block_Diagram | Method | Paper | Github | Year | FrameWork | Type | Dataset | Pretrained Model | Training Pipeline | Inference Pipeline | License | Keywords |
| 1 |  |
Unseen Object Amodal Instance Segmentation | <https://arxiv.org/pdf/2109.11103.pdf | https://github.com/gist-ailab/uoais | 2022 | PyTorch | Instance> Segmentation | UOAIS-SIM | Yes | Yes | Yes | Custom | List 3 elements (1) List 3 elements (2) * List 3 elements (3) |
| 2 |  |
Amodal Segmentation Based on Visible Region Segmentation and Shape Prior | <https://arxiv.org/pdf/2012.05598.pdf | https://github.com/YutingXiao/Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | 2020 | PyTorch | Instance> Segmentation | D2SA.KINS,COCOA Cls | Yes | Yes | Yes | NA | KY |
| 3 |  |
Watch and Learn 2D Amodal Representation using time-lapse imagery | <https://ieeexplore.ieee.org/document/9878958 | https://github.com/dineshreddy91/WALT | 2022 | PyTorch | Instance> Segmentation | WALT | Yes | Yes | Yes | MIT | KY |
| 4 |  |
Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers | <https://arxiv.org/abs/2103.12340 | https://github.com/lkeab/BCNet | 2021 | PyTorch | Instance> Segmentation | COCOA , COCO,COCO-OCC, KINS | Yes | Yes | Yes | MIT | KY |
| 5 |  |
Amodal Instance Segmentation and Multi-Object Tracking with Deep Pixel Embeddings | <https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1125&context=elecengtheses | https://github.com/yanfengliu/embedding_tracking | 2019 | TensorFlow | Instance> Segmentation | MOT | No | No | Yes | NA | KY |
| 6 |  |
Amodal Completion for Estimating Centers of Grapes | <https://drive.google.com/file/d/1RlYYrtNAfvKLiXu55iUw62KNdhcr1ZMb/view | https://github.com/julianlegouic/grape-amodal-completion | 2020 | PyTorch | Instance> Segmentation | synthetic grape dataset | No | Yes | Yes | NA | KY |
| 7 | NA | Amodal Segmentation through Out-of-Task and Out-of-Distribution Generalization with a Bayesian Model Y | <https://arxiv.org/pdf/2010.13175.pdf | https://github.com/YihongSun/Bayesian-Amodal | 2022 | PyTorch | Instance> Segmentation | KINS, COCOACls,OccludedVehicle | Yes | Yes | Yes | MIT | KY |
| 8 |  |
Learning Semantics-aware Distance Map with Semantics Layering Network for Amodal Instance Segmentation | <https://arxiv.org/pdf/1905.12898.pdf | https://github.com/apchenstu/SLN-Amodal | 2019 | PyTorch | Instance> Segmentation | COCOA Cls, D2SA | Yes | Yes | Yes | MIT | KY |
| 9 |  |
Amodal Instance Segmentation with Transformer | <https://arxiv.org/pdf/2210.06323.pdf | https://github.com/UARK-AICV/AISFormer | 2022 | PyTorch | Instance> Segmentation | COCOA Cls,D2SA | Yes | Yes | Yes | Apache-2.0 | KY |
| 10 |  |
A Weakly Supervised Amodal Segmenter with Boundary Uncertainty Estimation | <https://arxiv.org/pdf/2108.09897.pdf | https://github.com/ducminhkhoi/Amodal-Instance-Seg-ASBU | 2021 | PyTorch | Instance> Segmentation | COCOA Cls,KINS | No | Yes | Yes | Apache-2.0 | KY |