STEm-Seg: Spatio-temporal Embeddings for Instance Segmentation in Videos

Existing methods for instance segmentation in videos typi-cally involve multi-stage pipelines that follow the tracking-by-detectionparadigm and model a video clip as a sequence of images. Multiple net-works are used to detect objects in individual frames, and then associatethese detections over time... (read more)

PDF Abstract ECCV 2020 PDF ECCV 2020 Abstract

Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
BENCHMARK
Unsupervised Video Object Segmentation DAVIS 2016 STEm-Seg J&F 80.6 # 4
Unsupervised Video Object Segmentation DAVIS 2017 (val) STEm-Seg J&F 64.7 # 2
Jaccard (Mean) 61.5 # 2
Jaccard (Recall) 70.4 # 2
Jaccard (Decay) -4 # 1
F-measure (Mean) 67.8 # 2
F-measure (Recall) 75.5 # 2
F-measure (Decay) 1.2 # 2

Methods used in the Paper


METHOD TYPE
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