Amodal Instance Segmentation
13 papers with code • 1 benchmarks • 2 datasets
Different from traditional segmentation which only focuses on visible regions, amodal instance segmentation also predicts the occluded parts of object instances.
Description Credit: Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers, CVPR'21
Libraries
Use these libraries to find Amodal Instance Segmentation models and implementations
WALT
MOViD-Amodal
Latest papers
A Unified Instance Segmentation Framework for Completely Occluded Objects and Dense Objects in Robot Vision Measurement
zhen6618/obbinstancesegmentation
•
•
In addition, since OBBs only serve as prompts, CFNet alleviates the over-dependence on bounding box detection performance of current instance segmentation methods using OBBs for dense objects.
SynTable: A Synthetic Data Generation Pipeline for Unseen Object Amodal Instance Segmentation of Cluttered Tabletop Scenes
In this work, we present SynTable, a unified and flexible Python-based dataset generator built using NVIDIA's Isaac Sim Replicator Composer for generating high-quality synthetic datasets for unseen object amodal instance segmentation of cluttered tabletop scenes.
Amodal Intra-class Instance Segmentation: Synthetic Datasets and Benchmark
Images of realistic scenes often contain intra-class objects that are heavily occluded from each other, making the amodal perception task that requires parsing the occluded parts of the objects challenging.
AISFormer: Amodal Instance Segmentation with Transformer
AISFormer explicitly models the complex coherence between occluder, visible, amodal, and invisible masks within an object's regions of interest by treating them as learnable queries.
WALT: Watch and Learn 2D Amodal Representation From Time-Lapse Imagery
dineshreddy91/WALT
•
•
CVPR 2022
Labeled real data of occlusions is scarce (even in large datasets) and synthetic data leaves a domain gap, making it hard to explicitly model and learn occlusions.
Unseen Object Amodal Instance Segmentation via Hierarchical Occlusion Modeling
gist-ailab/uoais
•
•
Instance-aware segmentation of unseen objects is essential for a robotic system in an unstructured environment.
A Weakly Supervised Amodal Segmenter with Boundary Uncertainty Estimation
ducminhkhoi/Amodal-Instance-Seg-ASBU
•
•
ICCV 2021
The resulting predictions on training images are taken as the pseudo-ground truth for the standard training of Mask-RCNN, which we use for amodal instance segmentation of test images.
Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers
lkeab/BCNet
•
•
CVPR 2021
Segmenting highly-overlapping objects is challenging, because typically no distinction is made between real object contours and occlusion boundaries.
Amodal Segmentation through Out-of-Task and Out-of-Distribution Generalization with a Bayesian Model
yihongsun/bayesian-amodal
•
•
CVPR 2022
Moreover, by leveraging an outlier process, Bayesian models can further generalize out-of-distribution to segment partially occluded objects and to predict their amodal object boundaries.
Layered Embeddings for Amodal Instance Segmentation
The proposed method extends upon the representational output of semantic instance segmentation by explicitly including both visible and occluded parts.
