29 citations · 60 across the 10 of their papers we have counts for
11 papers · 1 filter
iFS-RCNN: An Incremental Few-shot Instance Segmenter
Khoi Nguyen, Sinisa Todorovic
This paper addresses incremental few-shot instance segmentation, where a few examples of new object classes arrive when access to training examples of old classes is not available…
A Weakly Supervised Amodal Segmenter with Boundary Uncertainty Estimation
Khoi Nguyen, Sinisa Todorovic
This paper addresses weakly supervised amodal instance segmentation, where the goal is to segment both visible and occluded (amodal) object parts, while training provides only grou…
Action Shuffle Alternating Learning for Unsupervised Action Segmentation
Jun Li, Sinisa Todorovic
This paper addresses unsupervised action segmentation. Prior work captures the frame-level temporal structure of videos by a feature embedding that encodes time locations of frames…
Anchor-Constrained Viterbi for Set-Supervised Action Segmentation
Jun Li, Sinisa Todorovic
This paper is about action segmentation under weak supervision in training, where the ground truth provides only a set of actions present, but neither their temporal ordering nor w…
FAPIS: A Few-shot Anchor-free Part-based Instance Segmenter
Khoi Nguyen, Sinisa Todorovic
This paper is about few-shot instance segmentation, where training and test image sets do not share the same object classes. We specify and evaluate a new few-shot anchor-free part…
A Self-supervised GAN for Unsupervised Few-shot Object Recognition
Khoi Nguyen, Sinisa Todorovic
This paper addresses unsupervised few-shot object recognition, where all training images are unlabeled, and test images are divided into queries and a few labeled support images pe…