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. A fully convolutional network is trained to produce consistent pixel-level embedding across two layers such that, when clustered, the results convey the full spatial extent and depth ordering of each instance. Results demonstrate that the network can accurately estimate complete masks in the presence of occlusion and outperform leading top-down bounding-box approaches. Source code available at https://github.com/yanfengliu/layered_embeddings
Code (1)
Tasks
Amodal Instance SegmentationInstance SegmentationSegmentationSemantic SegmentationSimilar Papers 제목 키워드 기반
Foundation Models for Amodal Video Instance Segmentation in Automated Driving
In this work, we study amodal video instance segmentation for automated driving. Previous works perform amodal video instance segmentation relying on methods trained on entirely labeled video data with techniques borrowe…
Amodal Instance SegmentationInstance SegmentationPoint TrackingSegmentation+2Learning to See the Invisible: End-to-End Trainable Amodal Instance Segmentation
Semantic amodal segmentation is a recently proposed extension to instance-aware segmentation that includes the prediction of the invisible region of each object instance. We present the first all-in-one end-to-end traina…
Amodal Instance SegmentationData AugmentationInstance SegmentationSegmentation+1Amodal Instance Segmentation
We consider the problem of amodal instance segmentation, the objective of which is to predict the region encompassing both visible and occluded parts of each object. Thus far, the lack of publicly available amodal segmen…
Amodal Instance SegmentationInstance SegmentationSegmentationSemantic SegmentationA2VIS: Amodal-Aware Approach to Video Instance Segmentation
Handling occlusion remains a significant challenge for video instance-level tasks like Multiple Object Tracking (MOT) and Video Instance Segmentation (VIS). In this paper, we propose a novel framework, Amodal-Aware Video…
Instance SegmentationMultiple Object TrackingObjectObject Tracking+3AISFormer: Amodal Instance Segmentation with Transformer
Amodal Instance Segmentation (AIS) aims to segment the region of both visible and possible occluded parts of an object instance. While Mask R-CNN-based AIS approaches have shown promising results, they are unable to mode…
Amodal Instance SegmentationDecoderInstance SegmentationSegmentation+1