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Found 5 papers, 2 papers with code
Continual Segmentation with Disentangled Objectness Learning and Class Recognition
Based on these findings, we propose CoMasTRe by disentangling continual segmentation into two stages: forgetting-resistant continual objectness learning and well-researched continual classification.
Weight-guided class complementing for long-tailed image recognition
In this paper, we propose a Weight-Guided Class Complementing framework to address this issue.
Ranked #11 on
Long-tail Learning
on CIFAR-10-LT (ρ=100)
Democracy Does Matter: Comprehensive Feature Mining for Co-Salient Object Detection
To achieve this, we design a democratic prototype generation module to generate democratic response maps, covering sufficient co-salient regions and thereby involving more shared attributes of co-salient objects.
Ranked #3 on
Co-Salient Object Detection
on CoCA
Fast Pixel-Matching for Video Object Segmentation
Most mask-propagation based models are faster but with relatively low performance due to failure to adapt to object appearance variation.
Structure-Consistent Weakly Supervised Salient Object Detection with Local Saliency Coherence
Since scribble labels fail to offer detailed salient regions, we propose a local coherence loss to propagate the labels to unlabeled regions based on image features and pixel distance, so as to predict integral salient regions with complete object structures.
