Xiangtai Li
Xiangtai Li
MMLab@NTU, S-Lab, Nanyang Technological University
Verified email at - Homepage
Cited by
Cited by
Semantic flow for fast and accurate scene parsing
X Li, A You, Z Zhu, H Zhao, M Yang, K Yang, S Tan, Y Tong
ECCV (oral), 2020
Involution: Inverting the Inherence of Convolution for Visual Recognition
D Li, J Hu, C Wang, X Li, Q She, L Zhu, T Zhang, Q Chen
CVPR, 2021
Improving semantic segmentation via decoupled body and edge supervision
X Li, X Li, L Zhang, G Cheng, J Shi, Z Lin, S Tan, Y Tong
ECCV, 2020
Dual graph convolutional network for semantic segmentation
L Zhang*, X Li*, A Arnab, K Yang, Y Tong, PHS Torr
BMVC, 2019
Gated Fully Fusion for Semantic Segmentation
X Li, H Zhao, L Han, Y Tong, S Tan, K Yang
AAAI (oral), 2020
PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation
X Li, H He, X Li, G Cheng, J Shi, L Weng, Y Tong, Z Lin
CVPR, 2021
Global aggregation then local distribution for scene parsing
X Li, L Zhang, G Cheng, K Yang, Y Tong, X Zhu, T Xiang
IEEE-TIP, 2021
End-to-end video object detection with spatial-temporal transformers
L He, Q Zhou, X Li, L Niu, G Cheng, X Li, W Liu, Y Tong, L Ma, L Zhang
ACM-MM, 2021
TransVOD: end-to-end video object detection with spatial-temporal transformers
Q Zhou*, X Li*, L He, Y Yang, G Cheng, Y Tong, L Ma, D Tao
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
Video K-Net: A Simple, Strong, and Unified Baseline for Video Segmentation
X Li, W Zhang, J Pang, K Chen, G Cheng, Y Tong, CC Loy
CVPR (oral), 2022
Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network?
Y Yang, S Chen, X Li, L Xie, Z Lin, D Tao
NeurIPS, 2022
Enhanced Boundary Learning for Glass-like Object Segmentation
X Li*, H He*, G Cheng, J Shi, Y Tong, G Meng, V Prinet, L Weng
ICCV, 2021
Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class Incremental Learning
Y Yang, H Yuan, X Li, Z Lin, P Torr, D Tao
ICLR-spotlight, 2023
Transformer-based visual segmentation: A survey
X Li, H Ding, W Zhang, H Yuan, J Pang, G Cheng, K Chen, Z Liu, CC Loy
arXiv preprint arXiv:2304.09854, 2023
Rethinking mobile block for efficient neural models
J Zhang, X Li, J Li, L Liu, Z Xue, B Zhang, Z Jiang, T Huang, Y Wang, ...
ICCV, 2023
Video semantic segmentation via sparse temporal transformer
J Li, W Wang, J Chen, L Niu, J Si, C Qian, L Zhang
Proceedings of the 29th ACM International Conference on Multimedia, 59-68, 2021
Panoptic-PartFormer: Learning a Unified Model for Panoptic Part Segmentation
X Li, S Xu, G Cheng, Y Yibo, Y Tong, D Tao
ECCV, 2022
PolyphonicFormer: Unified Query Learning for Depth-aware Video Panoptic Segmentation
H Yuan*, X Li*, Y Yang, G Cheng, J Zhang, Y Tong, L Zhang, D Tao
ECCV; Winner of ICCV-2021-BMTT workshop-2rd track, 2022
Fashionformer: A Simple, Effective and Unified Baseline for Human Fashion Segmentation and Recognition
X Li*, S Xu*, J Wang, G Cheng, Y Tong, D Tao
ECCV, 2022
Convolution-enhanced Evolving Attention Networks
Y Wang, Y Yang, Z Li, J Bai, M Zhang, X Li, J Yu, C Zhang, G Huang, ...
T-PAMI, 2022
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