34 citations · 80 across the 11 of their papers we have counts for
13 papers
RMP-SAM: Towards Real-Time Multi-Purpose Segment Anything
Shilin Xu, Haobo Yuan, Qingyu Shi +9
Recent segmentation methods, which adopt large-scale data training and transformer architecture, aim to create one foundation model that can perform multiple tasks. However, most o…
Neural Collapse Terminus: A Unified Solution for Class Incremental Learning and Its Variants
Yibo Yang, Haobo Yuan, Xiangtai Li +6
How to enable learnability for new classes while keeping the capability well on old classes has been a crucial challenge for class incremental learning. Beyond the normal case, lon…
ShadowNet for Data-Centric Quantum System Learning
Yuxuan Du, Yibo Yang, Tongliang Liu +3
Understanding the dynamics of large quantum systems is hindered by the curse of dimensionality. Statistical learning offers new possibilities in this regime through neural network…
Towards Open Vocabulary Learning: A Survey
Jianzong Wu, Xiangtai Li, Shilin Xu +9
In the field of visual scene understanding, deep neural networks have made impressive advancements in various core tasks like segmentation, tracking, and detection. However, most a…
Problem-Dependent Power of Quantum Neural Networks on Multi-Class Classification
Yuxuan Du, Yibo Yang, Dacheng Tao +1
Quantum neural networks (QNNs) have become an important tool for understanding the physical world, but their advantages and limitations are not fully understood. Some QNNs with spe…
PanopticPartFormer++: A Unified and Decoupled View for Panoptic Part Segmentation
Xiangtai Li, Shilin Xu, Yibo Yang +6
Panoptic Part Segmentation (PPS) unifies panoptic and part segmentation into one task. Previous works utilize separate approaches to handle things, stuff, and part predictions with…
SFNet: Faster and Accurate Semantic Segmentation via Semantic Flow
Xiangtai Li, Jiangning Zhang, Yibo Yang +4
In this paper, we focus on exploring effective methods for faster and accurate semantic segmentation. A common practice to improve the performance is to attain high-resolution feat…
EATFormer: Improving Vision Transformer Inspired by Evolutionary Algorithm
Jiangning Zhang, Xiangtai Li, Yabiao Wang +4
Motivated by biological evolution, this paper explains the rationality of Vision Transformer by analogy with the proven practical evolutionary algorithm (EA) and derives that both…
Panoptic-PartFormer: Learning a Unified Model for Panoptic Part Segmentation
Xiangtai Li, Shilin Xu, Yibo Yang +3
Panoptic Part Segmentation (PPS) aims to unify panoptic segmentation and part segmentation into one task. Previous work mainly utilizes separated approaches to handle thing, stuff,…
ART-Point: Improving Rotation Robustness of Point Cloud Classifiers via Adversarial Rotation
Robin Wang, Yibo Yang, Dacheng Tao
Point cloud classifiers with rotation robustness have been widely discussed in the 3D deep learning community. Most proposed methods either use rotation invariant descriptors as in…
Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network?
Yibo Yang, Shixiang Chen, Xiangtai Li +3
Modern deep neural networks for classification usually jointly learn a backbone for representation and a linear classifier to output the logit of each class. A recent study has sho…
PolyphonicFormer: Unified Query Learning for Depth-aware Video Panoptic Segmentation
Haobo Yuan, Xiangtai Li, Yibo Yang +5
The Depth-aware Video Panoptic Segmentation (DVPS) is a new challenging vision problem that aims to predict panoptic segmentation and depth in a video simultaneously. The previous…
Dual-Flow Transformation Network for Deformable Image Registration with Region Consistency Constraint
Xinke Ma, Yibo Yang, Yong Xia +1
Deformable image registration is able to achieve fast and accurate alignment between a pair of images and thus plays an important role in many medical image studies. The current de…