128 citations · 620 across the 55 of their papers we have counts for
11 papers · 1 filter
Slot-VPS: Object-centric Representation Learning for Video Panoptic Segmentation
Yi Zhou, Hui Zhang, Hana Lee +6
Video Panoptic Segmentation (VPS) aims at assigning a class label to each pixel, uniquely segmenting and identifying all object instances consistently across all frames. Classic so…
Recursive Least-Squares Estimator-Aided Online Learning for Visual Tracking
Jin Gao, Yan Lu, Xiaojuan Qi +5
Tracking visual objects from a single initial exemplar in the testing phase has been broadly cast as a one-/few-shot problem, i.e., one-shot learning for initial adaptation and few…
ST3D++: Denoised Self-training for Unsupervised Domain Adaptation on 3D Object Detection
Jihan Yang, Shaoshuai Shi, Zhe Wang +2
In this paper, we present a self-training method, named ST3D++, with a holistic pseudo label denoising pipeline for unsupervised domain adaptation on 3D object detection. ST3D++ ai…
Multilevel Knowledge Transfer for Cross-Domain Object Detection
Botos Csaba, Xiaojuan Qi, Arslan Chaudhry +2
Domain shift is a well known problem where a model trained on a particular domain (source) does not perform well when exposed to samples from a different domain (target). Unsupervi…
Fully Convolutional Networks for Panoptic Segmentation with Point-based Supervision
Yanwei Li, Hengshuang Zhao, Xiaojuan Qi +6
In this paper, we present a conceptually simple, strong, and efficient framework for fully- and weakly-supervised panoptic segmentation, called Panoptic FCN. Our approach aims to r…
Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigation
Ruifei He, Jihan Yang, Xiaojuan Qi
While self-training has advanced semi-supervised semantic segmentation, it severely suffers from the long-tailed class distribution on real-world semantic segmentation datasets tha…