6 citations · 7 across the 7 of their papers we have counts for
7 papers
When do modal definability and preservation theorems transfer to the finite?
Johan van Benthem, Balder ten Cate, Xi Yang
We study which classic modal definability and preservation results survive when attention is restricted to finite structures, where many first-order transfer theorems are known to…
Lightweight RGB-D Salient Object Detection from a Speed-Accuracy Tradeoff Perspective
Songsong Duan, Xi Yang, Nannan Wang +1
Current RGB-D methods usually leverage large-scale backbones to improve accuracy but sacrifice efficiency. Meanwhile, several existing lightweight methods are difficult to achieve…
SA3DIP: Segment Any 3D Instance with Potential 3D Priors
Xi Yang, Xu Gu, Xingyilang Yin +1
The proliferation of 2D foundation models has sparked research into adapting them for open-world 3D instance segmentation. Recent methods introduce a paradigm that leverages superp…
Point Deformable Network with Enhanced Normal Embedding for Point Cloud Analysis
Xingyilang Yin, Xi Yang, Liangchen Liu +2
Recently MLP-based methods have shown strong performance in point cloud analysis. Simple MLP architectures are able to learn geometric features in local point groups yet fail to mo…
Gradient constrained sharpness-aware prompt learning for vision-language models
Liangchen Liu, Nannan Wang, Dawei Zhou +4
This paper targets a novel trade-off problem in generalizable prompt learning for vision-language models (VLM), i.e., improving the performance on unseen classes while maintaining…
Towards Semi-Supervised Deep Facial Expression Recognition with An Adaptive Confidence Margin
Hangyu Li, Nannan Wang, Xi Yang +2
Only parts of unlabeled data are selected to train models for most semi-supervised learning methods, whose confidence scores are usually higher than the pre-defined threshold (i.e.…
Saliency deep embedding for aurora image search
Xi Yang, Xinbo Gao, Bin Song +2
Deep neural networks have achieved remarkable success in the field of image search. However, the state-of-the-art algorithms are trained and tested for natural images captured with…