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Found 5 papers, 1 papers with code
Unsupervised and semi-supervised co-salient object detection via segmentation frequency statistics
Our unsupervised model is a great pre-training initialization for our semi-supervised model SS-CoSOD, especially when very limited labeled data is available for training.
Pose-Guided Knowledge Transfer for Object Part Segmentation
Object part segmentation is an important problem for many applications, but generating the annotations to train a part segmentation model is typically quite labor-intensive.
HOPE-Net: A Graph-based Model for Hand-Object Pose Estimation
Hand-object pose estimation (HOPE) aims to jointly detect the poses of both a hand and of a held object.
Gated Feedback Refinement Network for Coarse-to-Fine Dense Semantic Image Labeling
In order to address this issue, we also propose Gated Feedback Refinement Network (G-FRNet) that addresses this limitation.
Label Refinement Network for Coarse-to-Fine Semantic Segmentation
We propose a novel network architecture called the label refinement network that predicts segmentation labels in a coarse-to-fine fashion at several resolutions.
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